Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Fronted End Central Process Integration Senior Engineer

Solution Architect, Cargo Management Systems

Application Developer - Fullstack Developer

AVP, Solution Architect

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Intermediate App Developer – Production Engineering, Java

Responsibilities: Deploy and Land: <ul><li>Own end-to-end delivery of AI and analytics products at stations in your region.</li><li>Cover discovery, scoping, development, integration, user acceptance testing (UAT), hypercare and rollout.</li><li>Embed with operations.</li><li>Participate in business stand-ups.</li><li>Visit the ramp and cargo floor.</li><li>Understand local data realities rather than making assumptions.</li><li>Ship production code in Python and comparable stacks against live flight, cargo, workforce and equipment data.</li><li>Avoid handing over prototypes for someone else to productionise.</li><li>Scale deployment by reducing the cost and time required to deploy solutions across additional stations.</li><li>Achieve this through reusable integrations, configuration and runbooks.</li></ul> Build on the Platform, Not Around It: <ul><li>Consume data through the semantic layer and governed data platform.</li><li>Avoid parallel pipelines, local definitions and workarounds.</li><li>Apply Centre of Excellence (CoE) patterns and guardrails.</li><li>Follow reference architectures, AI registry, human-in-the-loop controls, access and residency rules.</li><li>Integrate GenAI and ML into workflows.</li><li>Implement RAG and retrieval patterns.</li><li>Implement agentic and tool-use patterns.</li><li>Apply evaluation frameworks.</li><li>Establish observability.</li><li>Maintain production cost control.</li></ul> Make Insight Self-Service: <ul><li>Build data products, not report queues.</li><li>Design governed, reusable datasets and semantic models.</li><li>Enable operations teams, airlines and forwarders to answer their own questions.</li><li>Put insight in front of the customer.</li><li>Deliver station and customer-facing analytics.</li><li>Enable natural-language access to operational data.</li><li>Ensure appropriate access, residency and confidentiality controls.</li><li>Design for the user, not the requester.</li><li>Ensure every product identifies the decision it changes and the person responsible for making it.</li><li>Instrument usage.</li><li>Retire products that are not used.</li><li>Consolidate fragmented reporting rather than extending it.</li></ul> Close the Loop: <ul><li>Feed field learnings back.</li><li>Convert integration problems into hardened patterns for the CoE and requirements for the platform team.</li><li>Own adoption and benefits.</li><li>Instrument deployments.</li><li>Track usage and benefits against the business case.</li><li>Report results accurately.</li><li>Be the technical face to the business and customers.</li><li>Translate between operations, the CoE and platform engineering.</li><li>Success in the First 12 Months</li></ul> Requirements: Experience: <ul><li>6+ years of experience in software or ML engineering.</li><li>Experience must include customer-facing or business-embedded delivery.</li><li>Demonstrated track record of scoping and delivering complex systems end to end in ambiguous, fast-moving environments.</li><li>Ability to remain accountable after go-live.</li><li>Production experience with LLM or ML systems.</li><li>Experience with prompt and agent design.</li><li>Experience with RAG.</li><li>Experience with evaluation frameworks.</li><li>Experience with deployment at scale.</li><li>Understanding of how model behaviour influences product experience.</li><li>Strong Python and API development skills.</li><li>Experience with FastAPI or equivalent.</li><li>Comfortable working across backend and frontend development.</li><li>Ability to build a working system independently.</li><li>Practical experience with Docker.</li><li>Practical experience with Kubernetes.</li><li>Practical experience with CI/CD.</li><li>Practical experience with cloud data platforms.</li><li>Experience integrating batch and real-time data against complex enterprise data sources.</li><li>Strong understanding of analytics.</li><li>Experience with semantic and dimensional modelling.</li><li>Knowledge of modern BI.</li><li>Experience designing data products that non-technical and external users can operate independently.</li><li>Aviation, logistics or complex operations experience is advantageous but not mandatory.</li><li>Willingness to learn operations directly from the operational floor is essential.</li></ul> Qualifications: <ul><li>Bachelors, MSc or PhD in Computer Science, Engineering, Mathematics or a related field.</li></ul>

Responsibilities: <ul><li>Own end-to-end delivery of AI and analytics products at stations in your region: discovery, scoping, build, integration, UAT, hypercare and rollout.</li><li>Embed with the operation. Sit in business stand-ups, walk the ramp and the cargo floor, and specify the local data reality rather than assuming it.</li><li>Ship production code in Python and comparable stacks against live flight, cargo, workforce and equipment data, not prototypes handed to someone else to productionise.</li><li>Scale deployment. Reduce cost and time-to-deploy from station N to station N+1 through reusable integrations, configuration and runbooks.</li><li>Consume through the semantic layer and the governed data platform. No parallel pipelines, no local definitions, no workarounds.</li><li>Apply CoE patterns and guardrails: reference architectures, AI registry, human-in-the-loop controls, access and residency rules.</li><li>Integrate GenAI and ML into workflows: RAG and retrieval, agentic and tool-use patterns, evaluation frameworks, observability and cost control in production.</li><li>Build data products, not report queues. Design- governed, reusable datasets and semantic models that let operations, airlines and forwarders answer their own questions.</li><li>Put insight in front of the customer. Deliver station and customer-facing analytics, including natural-language access to operational data, with the access, residency and confidentiality controls customer data demands.</li><li>Design for the user, not the requester. Every product names the decision it changes and who makes it. Instrument usage, retire what nobody opens, consolidate the long tail rather than extend it.&nbsp;</li><li>Feed the field back. Every integration problem you solve becomes a hardened pattern for the CoE and a requirement for the platform team.</li><li>Own adoption and benefits. Instrument what you deploy, track usage and benefit against the business case, and report it honestly.</li><li>Be the technical face to the business and to customers, translating between operations, the CoE and platform engineering.&nbsp;</li></ul> Requirements:&nbsp; <ul><li>6+ years in software or ML engineering, including customer-facing or business-embedded delivery.</li><li>Track record of scoping and shipping complex systems end to end in ambiguous, fast-moving environments, and staying accountable after go-live.</li><li>Production experience with LLM or ML systems: prompt and agent design, RAG, evaluation frameworks, deployment at scale, and an understanding of how model behaviour shapes product experience.</li><li>Strong Python and API development (FastAPI or equivalent); comfortable across backend and front-end enough to build a working system alone.</li><li>Practical depth in Docker, Kubernetes, CI/CD, and cloud data platforms; batch and real-time integration against messy enterprise sources.</li><li>Fluency in the analytics half of the job: semantic and dimensional modelling, modern BI, and designing data products that non-technical and external users can operate without help.</li><li>Aviation, logistics or complex operations exposure is an advantage, not a prerequisite. Willingness to learn the operation from the floor is not optional.</li><li>Bachelors, MSc or PhD in Computer Science, Engineering, Mathematics or related field.&nbsp;</li></ul>

Responsibilities: <ul><li>Collaborate with multi-functional network teams from PIE, Process &amp; Equipment Engineering, WLR, TD to improve product yields and reliability within your assigned process loop.</li><li>May require travel to global company sites to foster collaboration and drive execution.</li><li>Communicate module related issues to the Fab engineering and leadership teams.</li><li>Design, execute, and analyze experiments to improve fab process, yield, and quality.</li><li>Collect and interpret complex data to optimize Fab processes and increase yields.</li><li>Engage and/or lead cross-area engineering teams to tackle process issues.</li><li>Work closely with global partners to stay ahead of on module related topics and process alignment projects.</li><li>Collaborate with other PI module owners and sister fabs to drive business process alignment</li><li>Partner with IE, Process and Equipment Engineering and Production to better forecast and balance yield, output and process issues</li><li>Promote network synergy through improved benchmarking and standardization of known engineering best-known methods (BKMs), business process.</li></ul> Requirements: <ul><li>Bachelor’s or advanced degree in Engineering or Science is required</li><li>Strong analytical, logical, and critical thinking skills</li><li>Effective communicator, able to collaborate across all levels</li><li>Growth mindset with a passion for continuous learning</li><li>Internship or experience in the semiconductor industry is a plus</li><li>Demonstrated leadership and a track record of impact are highly desirable</li><li>Interest in and knowledge of the semiconductor industry and company is preferred.</li></ul>

Responsibilities Target State Architecture and Convergence <ul><li>Define and maintain the target state architecture for cargo management systems across the global network, covering platform selection, consolidation, integration, and retirement</li><li>Produce a roadmap that sequences how regional systems (Cargospot, COSYS+, ePic) move toward an agreed target, with clear architectural rationale for each decision</li><li>Document and govern architecture decisions to ensure transparency, consistency, and auditability</li><li>Maintain a current-state map of the platform estate, including capability overlap, integration debt, and footprint reduction opportunities</li></ul> Integration, Connectivity, and Data Architecture <ul><li>Define integration standards and patterns for cargo systems, including airline connectivity (ONE Record, Cargo-XML, EDI), messaging, and API design</li><li>Set the data architecture for the cargo estate so that operational, customer, and commercial data flows are consistent and reusable across stations</li><li>Establish interoperability requirements between cargo management systems and adjacent platforms</li><li>Govern the technical aspects of customer-specific connectivity so that customer requests are met without fragmenting the core platform</li></ul> Change Order Validation and Cost Governance <ul><li>Review and validate every material change order raised against the cargo management systems are justified by the actual scope of work</li><li>Assess the technical complexity of each change order independently to challenge vendor proposals where required</li><li>Challenge inflated, padded, or over-scoped change orders, and provide documented technical rationale of its decisions</li><li>Distinguish change orders that reflect genuine new scope from those that should fall within existing contractual obligations or standard product, protecting the network from avoidable cost</li><li>Maintain a defensible record of change-order assessments so that platform spend is traceable and auditable, and patterns of vendor over-scoping are visible to leadership</li></ul> Standards, Governance, and Technical Authority <ul><li>Own the architectural standards that regional implementations are held against, and run the technical review of material platform changes</li><li>Provide architectural input into product governance</li><li>Ensure vendor solution designs align with target architecture or introduce avoidable lock-in</li><li>Partner with cybersecurity and enterprise architecture functions to ensure cargo platform architecture meets security, audit, and regulatory requirements</li></ul> Delivery Partnership and Advisory <ul><li>Act as the senior technical advisor to the Digital Product Management function, translating strategic direction into an executable systems blueprint</li><li>Support platform evaluations and proofs of concept with rigorous technical assessment</li><li>Provide architectural guidance to regional technology teams during implementation, migration, and cutover</li><li>Communicate architecture clearly and plainly to non-technical leadership; state platform status honestly as live, in build, in pilot, or proposed</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, Information Systems, or related discipline required; postgraduate qualification preferred</li><li>Recognised enterprise architecture certification valued: TOGAF 9.2 or equivalent</li><li>Cargo Systems Domain (required): Deep, hands-on knowledge of cargo management systems and the cargo handling business is essential and non-negotiable for this role; ideally across more than one of Cargospot, COSYS+, or ePic, with a clear understanding of how these systems are used at station level in export, import, and special-handling flows.</li><li>This knowledge is the basis on which the role validates change orders and holds the architectural line</li><li>Change Order and Cost Assessment: Demonstrated ability to assess vendor change orders on cost, man-hour estimate, and technical complexity, and to challenge estimates that are not justified by the work; able to translate a technical scope into a defensible commercial judgement</li><li>Solution and Systems Architecture: 10 or more years in technology delivery with a minimum 5 years in a solution or systems architecture role for enterprise operational platforms</li><li>Integration and Connectivity: Strong practical experience with integration architecture, API design, and airline connectivity standards (ONE Record, Cargo-XML, EDI, IATA messaging)</li><li>Platform Convergence: Demonstrated experience consolidating or rationalising a multi-system estate, including migration sequencing and footprint reduction</li><li>Vendor Engagement: Proven experience evaluating and challenging platform vendors on architecture, integration, and total cost</li><li>Cross-Regional Delivery: Experience operating across APAC, EMEA, and Americas with the cultural fluency to navigate regional system ownership and variation</li><li>Sector Experience: Aviation, cargo, logistics, or other 24/7/365 operational environment strongly preferred</li></ul>

Responsibilities: Application Development: <ul><li>Design, develop, test, deploy, and support web applications using Angular/AngularJS, Python, and modern full stack technologies.</li><li>Build responsive, high-performing, and user-friendly web interfaces.</li><li>Develop and maintain backend services, business logic, RESTful APIs, and system integrations.</li><li>Integrate applications with databases, enterprise platforms, and third-party systems.&nbsp;</li></ul> Solution Design: <ul><li>Analyze business and functional requirements and translate them into technical solutions.</li><li>Prepare technical designs, system workflows, and application specifications.</li><li>Contribute to technical design discussions and recommend scalable, maintainable solutions aligned with established architecture standards.</li><li>Support the evaluation and selection of appropriate technologies and development approaches.</li></ul> System Integration &amp; Database Management: <ul><li>Develop and maintain secure REST APIs and system integrations.</li><li>Design, optimize, and support relational databases and SQL queries.</li><li>Ensure secure, accurate, and reliable data processing across applications.</li><li>Monitor and optimize application, API, and database performance.</li></ul> Quality Assurance &amp; Testing: <ul><li>Develop and execute unit tests, integration tests, and defect resolution activities.</li><li>Participate in code reviews and quality improvement initiatives.</li><li>Support user acceptance testing, release validation, and production deployments.</li><li>Contribute to automated testing and continuous integration practices where applicable.</li></ul> Application Support &amp; Continuous Improvement: <ul><li>Troubleshoot application issues and provide timely resolution of incidents and defects.</li><li>Monitor application performance, availability, and operational health.</li><li>Perform root cause analysis and implement sustainable solutions to prevent recurring issues.</li><li>Identify opportunities to improve application functionality, performance, maintainability, and user experience.</li></ul> Agile Delivery &amp; Collaboration: <ul><li>Participate in backlog refinement, sprint planning, daily stand-ups, reviews, and retrospectives.</li><li>Collaborate with Business Analysts, Product Owners, Project Managers, and cross-functional technical teams.</li><li>Provide effort estimates and technical input to support project planning and delivery commitments.</li><li>Communicate progress, risks, dependencies, and technical recommendations to stakeholders.</li></ul> Security &amp; Development Standards: <ul><li>Follow secure software development practices and organizational security requirements.</li><li>Ensure applications comply with data privacy, security, audit, and compliance standards.</li><li>Adhere to coding standards, code review processes, and development best practices.</li><li>Support vulnerability remediation and application security improvements.</li></ul> Documentation &amp; Compliance; <ul><li>Maintain technical documentation, support guides, and system specifications.</li><li>Document application configurations, enhancements, integrations, and support procedures.</li><li>Ensure solutions are developed in accordance with organizational policies, standards, and governance requirements.</li></ul> Requirements: <ul><li>3+ years of software development experience, with strong hands-on expertise in Angular or AngularJS for web application development.</li><li>Strong experience in API development and integration, with the ability to develop, consume, test, and troubleshoot RESTful APIs.</li><li>Good working knowledge of JavaScript, TypeScript, HTML5, and CSS3, with a solid understanding of modern web application development practices.</li><li>Hands-on experience with SQL and relational databases, preferably SQL Server, PostgreSQL, or MySQL, including database queries and data handling.</li><li>Proficiency with Git/version control and good understanding of software development lifecycle, debugging, testing, and collaboration with cross-functional development teams.</li><li>Experience with Python development for backend services</li></ul>

Responsibilities: <ul><li>Influence many agile development teams through all phases of the Agile development life cycle through SAFe</li><li>Implement new technologies and assist developers as they migrate to new technologies</li><li>Architect applications across the full stack, experience in PCF, AWS, Cloud Native</li><li>Application Architecture, Microservices ecosystem, Spring Batch Apps using Spring Cloud Data Flow, J2EE, Spring Java, and RESTful APIs are a must.</li><li>Design data models to support complex business processes</li><li>Drive a CI/CD strategy using our Jenkins, Bitbucket, and uDeploy stack.</li><li>Influence and collaborate with software developers, UX designers, product managers, application architects, and customer application experts to create amazing apps.</li><li>Mentor and influence all levels of the team: in this role, you will have the opportunity to influence up and down the chain of command</li><li>Ensure compliance with architecture, security and technology standards set by company Financial</li><li>Assist in crafting and maintaining the future state technology architectural strategy, along with our application of modernization and migration roadmap.</li><li>Participate in Agile scrums consisting of cross-functional teams</li><li>Participate and Contribute towards Engineering Community of Practices (CoPs)</li><li>Lead Agile sprints as the technical expert, including sprint planning, daily standups, backlog grooming sessions, and sprint reviews</li><li>Ensure application code quality through development, test, and QA</li><li>Participate in addressing root cause analyses, incident reports and provide direction in problem resolution</li><li>Analyze production defects, troubleshoot systems, identify root cause, and implement fixes</li><li>Passionate about the latest technologies, open-source projects and languages</li><li>Provide 24x7 on-call support periodically throughout the year</li><li>Identify ways to increase efficiency and improve system performance</li><li>Work with third party vendors to develop software and/or integrate their software into the companys products</li></ul> Requirements: <ul><li>Bachelors degree in computer science or related degree with modern application</li><li>development experience, around 7 years of experience in Technology, 5+ years in</li><li>API development using Java and 2 years in Technical Lead driving product solutions in</li><li>Enterprise Communications</li><li>Strong Technical Expertise in Java, Spring Projects – Spring Boot, Spring Framework, Spring Cloud, Spring Batch, Spring Cloud Data Flow, S3 Bucket, Git, Maven, Gradle and REST</li><li>Prior experience working with US Payment networks (ACH, Wire, or related payment processing systems) is essential</li><li>Strong Experience in developing microservices with 12-factor app methodology</li><li>Strong Experience with Scaled Agile framework and familiarity with tools like JIRA Align</li><li>Strong Experience with Agile application development and familiarity with tools like JIRA</li><li>Strong Experience with continuous integration environments and using tools like Jenkins</li><li>Strong Experience writing unit and integration tests and familiarity with frameworks like Junit, Mockito, Spring Test.</li><li>Strong Experience with Caching Systems – Redis/Gemfire.</li></ul>

Responsibilities: Software Development: <ul><li>Design, develop, test, and maintain scalable software applications using Java Spring Boot and JavaScript for backend and frontend development, respectively. Build clean, reusable, maintainable, and well-tested code following software engineering best practices.</li></ul> Full Stack Application Development: <ul><li>Develop end-to-end web and mobile applications using Java Spring Boot, React or React Native, backend APIs, database integrations, and modern UI frameworks to deliver intuitive user experiences.</li><li>Design and develop secure RESTful APIs, backend services, authentication mechanisms, and data access layers while ensuring application scalability and performance.</li></ul> AI Enable Engineering: <ul><li>Leverage AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, Claude, Amazon Q, or similar tools to improve engineering productivity.</li><li>Experience integrating LLM APIs or AI-powered capabilities into applications is desirable.</li></ul> Collabration: <ul><li>Collaborate with Product Managers, Business Analysts, UX Designers, QA Engineers, Architects, and cross-functional engineering teams to understand business requirements and deliver scalable software solutions.</li><li>Participate in sprint planning, technical discussions, estimation, backlog refinement, and Agile ceremonies.</li></ul> Testing &amp; Quality: <ul><li>Develop unit tests, integration tests, and participate in peer code reviews to ensure software quality, maintainability, reliability, and performance.</li><li>Follow secure coding standards and engineering best practices.</li></ul> Cloud &amp; Devops: <ul><li>Contribute to CI/CD pipelines and cloud-native application deployments using technologies such as Docker, Kubernetes, Azure, AWS, GitHub Actions, or Azure DevOps.</li></ul> Continous Improvement: <ul><li>Identify opportunities to improve software architecture, engineering standards, automation, developer productivity, and application performance.</li><li>Adopt AI-assisted engineering workflows and modern software development practices.</li></ul> Technical Support: <ul><li>Troubleshoot production issues, perform root cause analysis, and resolve application issues while ensuring minimal business disruption.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent practical experience).</li><li>3–5 years of professional software development experience.</li><li>Minimum 3+ years of hands-on full-stack development experience.</li><li>Experience developing production-grade web or mobile applications (not academic or personal projects).</li><li>Strong proficiency in Java Spring Boot and JavaScript.</li><li>Experience developing applications using React or React Native.</li><li>Experience developing backend services using Node.js or equivalent backend technologies.</li><li>Strong understanding of REST API development.</li><li>Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or equivalent.</li><li>Strong knowledge of Git and modern software engineering practices.</li><li>Experience working in Agile/Scrum teams.</li><li>Strong understanding of object-oriented programming, software design principles, and data structures.</li></ul>

Responsibilities: <ul><li>Develop and maintain automation scripts using Linux shell scripting, Python, or other relevant tools.</li><li>Develop and maintain the entire DevOps pipelines.</li><li>Ensure seamless deployment and integration between cloud/prem environments (AWS).</li><li>Integrate AI models into production environments using containerized platforms such as OpenShift.</li><li>Implement and maintain network security protocols to safeguard AI systems and data pipelines.</li><li>Collaborate with cross-functional teams to understand AI workflows and translate them into robust engineering solutions.</li><li>Monitor and optimize system performance, reliability, and scalability.</li><li>Support CI/CD processes and infrastructure for AI model deployment and updates.</li></ul> Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related field.</li><li>Bash and Unix/Linux command-line toolkit is a must-have.</li><li>Deep technical background, with hands-on experience in supporting CI/CD pipelines (Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA workflow, and Confluence).</li><li>Hands-on experience with OpenShift, Docker, Kubernetes.</li><li>Knowledge of cloud platforms (e.g. AWS) is a must-have.</li><li>Exposure to data and network security and compliance in AI systems.</li><li>Knowledge of API integration and microservices architecture.</li><li>Proficiency in Python used both for automation and ML-related tasks</li><li>Knowledge of Workflow Orchestrator, such as Ctrl-M</li><li>Good knowledge of Logging and Monitoring tools, such as Splunk and Geneos.</li><li>Experience with Observability framework, such as Langfuse, Elastic Stack, Grafana, Open Telemetry.</li><li>Understanding of Generative AI (e.g. prompt engineering, RAG pipelines) and Agentic AI concepts.</li></ul>

Responsibilities: People, Talent and Cross-Functional Collaboration:&nbsp; <ul><li>Ensure optimal staffing levels across front-end, back-end, full-stack, and platform specializations.&nbsp;</li><li>Hire, coach, and develop top-tier engineering talent.</li><li>Manage direct reports and technical leads, address performance issues promptly, and build strong relationships with Product, Design, Platform, Data, and agile train leadership to deliver cohesive, customer-focused solutions.</li><li>Community of Practice, Developer Experience and AI-Driven Engineering: As AI tooling becomes inseparable from modern engineering practice, own the convergence of Community of Practice standards and AI adoption as a single discipline.&nbsp;</li><li>Foster best practice adoption across the engineering community with AI tooling treated as a first-class part of the practice.</li><li>Define standards for responsible AI adoption — including when to use AI coding assistants, agents, skills, and MCP integrations versus traditional approaches.</li><li>Establish clear guidance on the distinction between AI Skills (deterministic capabilities) and Agents (autonomous, multi-step workflows). </li><li>Evaluate, pilot, and roll out AI tools (GitHub Copilot, Claude Code, Cursor, Windsurf, Continue.dev, Aider, Cline, Ollama). </li><li>Define governance for AI use in regulated financial services contexts including data handling, PII protection, IP compliance, and code provenance. </li><li>Track and measure the combined impact of CoP practices and AI adoption on cycle time, PR throughput, defect rates, and developer satisfaction.</li><li>System Architecture and Technical Direction: Own a modern view of system architecture spanning client, server, data, integration, and AI layers.&nbsp;</li><li>Champion patterns such as micro-frontends, BFF, event-driven, API-first, serverless, and composable architectures.&nbsp;</li><li>Partner with Enterprise Architects on platform alignment.&nbsp;</li><li>Guide trade-off decisions (monolith vs. microservices, sync vs. async, build vs. buy). Use AI-powered architecture tools to accelerate design exploration and generate ADRs.</li><li>Ensure teams document decisions so both humans and AI agents can reason about the system. </li><li>Understand how AI tools interact with system architecture — including RAG, vector databases, MCP integrations, and agentic workflows.</li></ul> Strategic Planning, Delivery and Operational Excellence:&nbsp; <ul><li>Ensure plans align with CoP goals, review quarterly commitments to flag risks early, and step in to resolve conflicts between product, design, and engineering.&nbsp;</li><li>Drive CI/CD best practices, ensure high-quality scalable solutions across the stack, and provide on-call support during escalations.&nbsp;</li><li>Support tech leads hands-on when needed, regardless of which layer of the stack the problem lives in.</li></ul> Requirements: <ul><li>Strong hands-on background in modern front-end technologies (ReactJS, TypeScript, NextJS, Cypress) as an anchor foundation, with working knowledge of back-end technologies, APIs, microservices, and data layer concepts.&nbsp;</li><li>Experience with AWS cloud services, CI/CD pipelines, and modern DevOps practices.&nbsp;</li><li>Proven ability to lead engineers working across the full stack.</li><li>Solid grounding in system architecture fundamentals — distributed systems, scalability, CAP trade-offs, caching, messaging, API design — and familiarity with modern patterns (micro-frontends, BFF, event-driven, CQRS, serverless, composable architectures).&nbsp;</li><li>Experience making and documenting architecture decisions (ADRs), with understanding of how AI-native architecture (RAG pipelines, vector databases, agent orchestration) differs from traditional architecture.</li><li>Hands-on experience with AI coding assistants (GitHub Copilot, Claude Code, Cursor, or equivalent) with clear understanding of the difference between AI Skills and Agents, familiarity with MCP (Model Context Protocol), RAG patterns, and experience defining AI usage guidelines and governance frameworks for regulated environments.&nbsp;</li><li>Awareness of the open-source AI tooling ecosystem (Continue.dev, Aider, Cline, Ollama).</li><li>Proven experience leading and growing high-performing engineering teams, running or contributing to a Community of Practice, and strong communication skills with the ability to influence across organizational levels.</li></ul>

Responsibilities: <ul><li>Monitor production environments and respond to operational alerts.</li><li>Execute operational runbooks and incident response procedures.</li><li>Support deployments and environment management.</li><li>Develop automation scripts and engineering tools.</li><li>Assist with root cause investigations.</li><li>Support database health and maintenance.</li><li>Participate in on-call rotations.</li><li>Collaborate with development teams to improve reliability.</li></ul> Requirements: <ul><li>4–8 years of software development experience.</li><li>Strong Java programming skills.</li><li>Experience with APIs and microservices.</li><li>Basic cloud experience (Azure/GCP).</li><li>Knowledge of monitoring tools.</li><li>Experience with Couchbase and PostgreSQL.</li><li>Strong analytical and debugging skills.</li></ul>

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21 api Jobs found

Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Fronted End Central Process Integration Senior Engineer

Solution Architect, Cargo Management Systems

Application Developer - Fullstack Developer

AVP, Solution Architect

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Intermediate App Developer – Production Engineering, Java

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Forward Deployed Senior Engineer, AI & Analytics

Senior AI Engineer

Fronted End Central Process Integration Senior Engineer

Solution Architect, Cargo Management Systems

Application Developer - Fullstack Developer

AVP, Solution Architect

Software Engineer – Ag & Trade

Enterprise Analytics – Machine Learning Ops/AI Projects (VP1)

VP, Engineering Manager

Intermediate App Developer – Production Engineering, Java

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