Senior Full Stack Gen AI Engineer/Technical Engagement Manager

Role overview

Engineering and delivery

• Design, build, test, deploy, support, and enhance production-grade full-stack applications, services, APIs, and reusable frontend components.
• Lead technical engagement, clarify business and client needs, translate requirements into solution designs, and coordinate delivery plans and teams.
• Track execution, estimates, risks, dependencies, integrations, and production readiness; communicate status and trade-offs to stakeholders.
• Support discovery workshops, solution walkthroughs, demos, and client discussions.

Production, data, and AI

• Productionize solutions and implement CI/CD, deployment, rollback, monitoring, observability, security, testing, and operational support.
• Design data models and integration patterns, and connect internal systems, third-party platforms, analytics services, and enterprise data sources.
• Contribute to LLM, agentic workflow, RAG, embeddings, and vector database capabilities where relevant.

Team quality

• Coach junior and mid-level engineers through design discussions, pair problem solving, code reviews, and development guidance.
• Promote standards for architecture, coding, testing, documentation, version control, security, and release management.

Education and experience

• Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or a related field.
• 5–10 years in full-stack development, software engineering, application engineering, or a closely related role.
• Experience delivering production-grade applications, owning technical workstreams, coordinating contributors, mentoring developers, and working with stakeholders.

Required technical qualifications

• Strong programming skills in Python and/or JavaScript/TypeScript and experience with a backend framework such as FastAPI, Flask, Django, Node.js, Express, or comparable technology.
• Strong React.js experience, solid SQL database understanding, and experience designing REST APIs, integrations, authentication, and authorization.
• Hands-on experience with Git, automated testing, CI/CD, Docker, and Azure, AWS, or GCP.
• Understanding of architecture, secure development, debugging, code quality, performance, deployment, monitoring, incident troubleshooting, and production support.

Preferred qualifications

• NoSQL familiarity is advantageous.
• Experience in oil and gas, energy, utilities, energy retail, or marketing analytics is preferred.
• Microservices, Kubernetes, distributed systems, messaging, event-driven architectures, and data-intensive or workflow applications are preferred experience.
• AI/ML or Generative AI application experience is preferred; familiarity with Azure OpenAI/OpenAI, LangChain, vector databases, or RAG is useful but not required.
• Consulting, client-facing delivery, technical project management, or engagement management experience is advantageous.