Title / Designation – Senior AI Engineer

Number of positions – 2

Duration - 6 months Contract + Possibility of an extension

Location – 100% Remote USA / Canada

Working Model – Remote

Number of Internal interviews with Nagarro – 1 OR 2

Client Interviews – 2

Mode of Interviews – Virtual

Tentative start date – ASAP

Experience Required – 8 – 10 Years

Must have Skills:

• 2+ years of experience developing and experimenting with LLMs.
• 8+ years of experience developing APIs with Python.
• Hands-on, daily use of AI-assisted and agentic coding tools (e.g., Claude Code, Cursor, GitHub Copilot, autonomous coding agents) to write and refactor code, automate workflows, and optimize engineering processes.
• Python (Strong), FastAPI (Strong), Prompt Engineering with LLMs (Strong), Architecture (Strong), Agentic coding tools.

Nice-to-Have Skills:

• Experience with LLM guardrails - Experience with LLM Frameworks (e.g., LangChain, LlamaIndex).
• Experience with LLM monitoring and observability.

Job Description:

• Strong experience with Python, particularly in building REST APIs using frameworks like FastAPI.
• Grounding in NLP and machine learning as they relate to building LLM systems.
• Strong experience working with key LLM models APIs (e.g., OpenAI, Anthropic).
• Experience building, deploying, and securing MCP servers at scale.
• Understanding of multi-agent systems and their applications in complex problem-solving scenarios.
• Designing and implementing RAG systems end to end: vector databases, semantic search, retrieval quality, and chunking strategy.
• Experience with prompt writing for various use cases.
• Experience with generative solutions released to prod, at scale, beyond POCs.
• Proficiency with server-side events, event-driven architectures, and messaging systems.
• Strong critical thinking and systems thinking skills, with experience debugging, optimizing, and making sound engineering decisions across complex backend systems, not just solving isolated problems.
• Solid understanding of security best practices for backend systems, including authentication and data protection.
• Experience developing AI/ML technologies within large and business critical applications.
• Building evaluation into LLM systems: eval harnesses, regression suites, LLM-as-judge, and offline/online quality metrics.