Sr. AI Engineer

NOTE: Utkrusht hires for tier1 VC backed companies in the US and India. Your application and assessments will apply for multiple such roles and will be valid for 6 months.

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What You’ll Do

Build massive scale AI Agentic orchestration platforms. Awesome scale. Awesome people to work with. No fluff. Here are some of the activities your day to day life will involve:

• Design & Build LLM Workflows:

  Create systems that score freeform answers, generate contextual feedback, and assist users in real time. Develop prompt templates and chaining strategies that improve relevance, reduce token usage, and mitigate hallucinations.

• RAG Pipeline Implementation & Optimization:

  Build and tune retrieval-augmented generation pipelines that fetch dynamic context from vector stores (e.g., Pinecone, Weaviate). Ensure low-latency, high-accuracy retrieval combined with LLM-driven generation to personalize experiences (e.g., mock interviews, code reviews). reduce token usage, and mitigate hallucinations.

• LLM Evaluation & Analysis:

  Define and implement evaluation frameworks covering accuracy, consistency, bias, and interpretability for model outputs. Automate evaluation pipelines that monitor LLM performance over time and flag failure modes.

• Agent-Based System Development:

  Build tool-augmented agents that can evaluate coding, system design, or reasoning questions, using frameworks like LangChain, AutoGen or LlamaIndex. Research and integrate new agent orchestration techniques to improve multi-step reasoning.

• Cross-Functional Collaboration:

  Partner with backend engineers (Go, FastAPI), frontend engineers (React) and product managers to iterate on features, gather user feedback, and refine in production. Participate in agile ceremonies—standups, sprint planning, retrospectives—and provide regular status updates.

• Stay Current & Innovate:

  Review state-of-the-art papers, benchmarks, and open-source tools (e.g., retrieval research, prompt optimization techniques). Prototype new ideas (e.g., advanced retrieval strategies, custom fine-tuning flows) and demonstrate their feasibility to the team.

Qualifications

• Agency and bias for action - you'll be a mis-fit if you need tasks to be defined.
• A natural curiosity towards building better computing systems
• Experience working with LLM workflows or AI agentic systems in production (1+ years of this is required)
• 4-7 years of experience after a relevant Bachelors of Engineering or Masters of Engineering degree (or equivalent)

What is on Offer

• Real Impact:

  Own and shape the AI features that power our flagship product, influencing quality improvements for thousands of users.

• Competitive Compensation:

  Market-aligned salary and meritocratic equity grants.

• Cutting-Edge Environment:

  Continuous exposure to SOTA research, with opportunities to prototype and ship innovative AI features.

• Collaborative Culture:

  Work alongside a small, dedicated team of engineers, researchers, and product leaders—everyone’s voice matters.

• Learning & Growth:

  Regular “Tech Talks”, knowledge-share sessions, and support for attending conferences or workshops.