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Senior AI Engineer

BlauGarnet

Pune

4-6 years

Today

$24.1K–30.1K/yr

Full-time

Hybrid

Skills Required

LLM

RAG

Vector Database

LLM evaluation frameworks

OpenAI

Anthropic

Gemini

LangChain

Claude Code

Azure OpenAI

Python

FastAPI

PostgreSQL

SQL embedding pipelines

Description

Senior hands-on AI engineering role at the core of Blaugarnet’s product. You will build the AI reasoning engine that powers trustworthy production systems.

Company: Blaugarnet

Role: Senior AI Engineer

Location: Pune, India (hybrid)

Experience

- 4-6 years of software engineering overall
- 2-3 years hands-on building AI/GenAI systems in production
- Strong backend skills in a modern typed/async stack
- AI-native development as default mode, using coding agents daily
- Deterministic orchestration of LLM workflows with control flow and guardrails
- Guardrails enforced outside the model
- RAG in production over messy real-world data
- Relational data modeling under correctness constraints
- Strong SQL / Postgres
- LLM API integration across OpenAI, Gemini, and Anthropic
- Async programming and solid API design
- Docker, Git, and CI/CD workflows
- Evaluation-harness design with eval sets, benchmarks, and regression checks
- Judgment about cost and performance trade-offs
- Startup temperament with high agency and comfort with ambiguity

Responsibilities

- Design and build the core LLM reasoning and orchestration engine
- Architect enterprise RAG pipelines over structured and unstructured data
- Develop AI automation pipelines that integrate with real business systems
- Build and maintain backend services powering data-heavy AI applications
- Make AI systems trustworthy in production through evaluation and guardrails




- Own cost and performance through tracking, enforcement, and heuristics
- Build MCP-compatible tools and integrations across providers
- Own CI/CD and containerised deployment of AI services
- Raise the bar through code review, mentoring, and technical deep-dives
- Contribute to internal and open-source AI tooling
- Engage with real customer context and feedback
- Help shape what the company builds, not just how

Additional Responsibilities

- Work directly with the Founding Engineer and close to the founders
- Set the technical bar for engineers who join after you
- Take a problem end to end without a fully specified ticket
- Keep close to customer context and feedback
- Build systems that are part of the product itself

Nice To Have

- Open-source contributions to the AI ecosystem
- Published technical writing on LLMs, RAG, or agents
- PyPI packages
- Public speaking on LLMs, RAG, or agents
- MCP tooling and agent-interoperability standards
- Cloud AI platforms such as GCP Vertex AI, AWS Bedrock, and Azure OpenAI
- Comfort driving coding agents to build and integrate a React / TypeScript frontend against API contracts
- Experience in regulated or high-stakes enterprise domains
- Early-stage startup experience

More Skills async services, LLM reasoning, orchestration, planning, tool use, memory, validation, enterprise RAG, pgvector, AI automation pipelines, workflow engines, decision logic,



data-quality logic, backend services, guardrails, benchmarks, token tracking, cost tracking, budget enforcement, model-selection heuristics, MCP-compatible tools, integrations, multimodal pipelines, Docker, GitHub Actions, code review, technical deep-dives, mentoring, internal AI tooling, open-source AI tooling, Cursor

Other

- Reports to the CEO
- Enterprise product is live in early access
- Small, early, and moving fast
- The AI is the product and the systems you build are the product itself
- Scope includes real ownership and a direct line to the founders
- Learn from a founder with 25 years of AI and product experience at Google and Adobe
- Customer-focused and deliberate hiring philosophy
- Competitive compensation: ₹20-25 LPA
- Compensation: ₹2,000,000 - ₹2,500,000 per year
- Full time

Prepare for this role Recommended resources to build the skills for this position. Sponsored.

Generative AI with Large Language Models

Coursera

Comprehensive LLM course covering transformer architecture, fine-tuning, RLHF, and deployment.

Python 3 Programming Specialization

Coursera

Intermediate Python covering classes, inheritance, APIs, and data processing.

Python for Everybody Specialization

Coursera

Learn Python from scratch — variables, data structures, web scraping, and databases.

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