Job Title: AI Developer (Generative AI / Agentic AI)
Org: SEI IMS ATOM
Level: AI Developer
Role Summary
The AI Developer will build and support
production-ready Generative AI solutions—including
RAG-based assistants and
agentic workflows—that integrate with enterprise data and applications. You will work with Tech Leads/Architects to translate solution designs into secure, scalable implementations with strong engineering practice, observability, and reusable components.
Key Responsibilities
- Build GenAI apps: Implement LLM-based features such as Q&A, summarization, extraction, and classification using prompt engineering and structured outputs.
- Implement RAG pipelines: Build ingestion + chunking + embeddings + retrieval flows using vector databases to ground answers in enterprise knowledge.
- Develop agent workflows: Create agentic automations (tool calling, task routing, multi-step workflows) using common frameworks/patterns.
- Enterprise integration: Integrate AI services with internal systems via APIs, auth, and approved access controls; follow enterprise engineering standards.
- Quality & monitoring: Add logging/telemetry and participate in evaluation/testing to catch regressions and ensure stable production behavior.
- Developer productivity: Use coding assistants (e.g., Copilot/Cursor-style) to accelerate development while maintaining clean code and reviews.
Experience
Required Qualifications
- 5+ years total IT/software engineering experience (enterprise applications, APIs, services).
- 2+ years hands-on AI/ML/GenAI experience, including building or supporting AI solutions beyond
Must-Have Technical Skills
- Python (strong); ability to build services, scripts, and automation.
- Experience with LLMs (APIs/providers) and understanding of risks like hallucinations and quality control.
- Hands-on RAG framework experience (vector DB + retrieval + grounding loop).
- Exposure to Agents / agentic AI patterns (tool calling, orchestration, task decomposition).
- Solid engineering fundamentals: APIs, version control, testing, troubleshooting, secure coding practices.
- Experience with MCP servers or MCP-style tool integrations.
Preferred / Nice To Have (Keep Optional For Hiring)
- Familiarity with FastAPI/Flask, Docker, CI/CD, and production monitoring patterns.
- Exposure to financial services or regulated data environments.
Behavioral Competencies
- Strong ownership and problem-solving; can translate requirements into working, testable software.
- Collaborative—works effectively with architects, product owners, and operations partners.
- Continuous learning mindset in GenAI and automation.
