Senior AI Engineer

Remote

Contracted

Mid Level

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.

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