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Artificial Intelligence Engineer
On-site
Kodiva.ai
Startup
Product
B2B
₹ 6-15 Lacs PA
Seed
Information Technology
Mumbai, Maharashtra, India
Post Status: Active
Permanent
19 applications
Experience: 2-4 Years
Skills
Prompt Engineering
CI/CD
NoSQL
Docker
AWS
React.js
Kubernetes
Python
LLM
High Level Design (HLD)
Low Level Design (LLD)
LangChain
RAG
Agentic AI
Vector Databases
Posted Today

About the job

We're looking for an AI Engineer who can build end-to-end — from designing intelligent agent workflows to shipping the full-stack applications that bring them to life. You'll work across the stack, integrating LLMs and AI agents into real products that users rely on. This is a hands-on role for someone who enjoys both the AI/ML side and the engineering rigor of building production systems.

What You'll Do

  • Design, build, and deploy AI agents and agentic workflows (tool use, function calling, multi-step reasoning, orchestration).

  • Develop full-stack applications — backend services, APIs, and responsive front-end interfaces — that integrate AI capabilities.

  • Work with LLMs and frameworks (e.g., LangChain, LlamaIndex, or similar) to build retrieval-augmented generation (RAG), prompt pipelines, and evaluation systems.

  • Integrate third-party APIs, vector databases, and model providers (OpenAI, Anthropic, open-source models) into production systems.

  • Optimize for latency, cost, reliability, and accuracy across AI features.

  • Collaborate with product and design teams to translate requirements into working features.

  • Write clean, testable, well-documented code and participate in code reviews.

What We're Looking For

  • 2–5 years of professional software engineering experience, with hands-on work building AI/LLM-powered features.

  • Demonstrated experience building AI agents or agentic systems (orchestration, tool integration, autonomous workflows).

  • Strong full-stack skills: proficiency in a backend language (Python, Node.js, Go, etc.) and a modern front-end framework (React, Next.js, Vue, etc.).

  • Solid understanding of working with LLM APIs, prompt engineering, and evaluation/testing of AI outputs.

  • Experience with databases (SQL/NoSQL) and familiarity with vector stores (Pinecone, Weaviate, pgvector, etc.).

  • Comfortable with cloud platforms (AWS, GCP, or Azure) and CI/CD practices.

  • Strong problem-solving skills and the ability to own features from concept to production.

Nice to Have

  • Experience with model fine-tuning, embeddings, or open-source model deployment.

  • Familiarity with containerization (Docker, Kubernetes).

  • Contributions to open-source AI projects or a portfolio of agent-based applications.