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Job Title: Software Engineer – AI Agents & Automation
Location: Bengaluru, Karnataka
Employment Type: Full-time
Experience Level: (1–3 years)
About the Role
We are looking for a curious and driven Software Engineer who wants to be at the center of the AI revolution – not just using AI, but building with it. You will design and develop AI agents that automate manual workflows, bring intelligence to existing product features, and help evolve our products into the AI era. You will also contribute to and work with open-source AI tools and frameworks as part of your day-to-day development.
What You’ll Do
– Design, build, and deploy AI agents that automate manual, repetitive, or complex tasks
– Work with LLM APIs (OpenAI, Anthropic, Gemini, or open-source models) to build intelligent features
– Develop agentic pipelines using frameworks like LangChain, LangGraph, CrewAI, or AutoGen
– Integrate AI agents into existing product workflows to “agentify” manual processes
– Build tool-use and function-calling capabilities so agents can interact with APIs, databases, and systems
– Upgrade existing product features by layering in AI-powered enhancements
– Evaluate agent performance, improve prompt engineering, and iterate on reliability
– Collaborate with product and research teams to identify automation opportunities
– Write clean, testable, and well-documented code that others can build on
Must-Have (Non-Negotiable)
Education: B.Tech/M.Tech in Computer Science, IT, or a related field
Experience: 1–2 years of hands-on software development experience
Programming: Strong proficiency in Python – your primary language for agent development
AI/ML Awareness: Working knowledge of LLMs, prompt engineering, and AI APIs
Agent Frameworks: Hands-on exposure to at least one framework – LangChain, CrewAI, AutoGen, or LangGraph
APIs & Integration: Comfortable building and consuming REST APIs to connect agents with external systems
CS Fundamentals: Solid grasp of data structures, algorithms, and software design principles
Version Control: Proficient with Git – branching, pull requests, and code reviews
Good-to-Have (Strong Plus)
RAG Pipelines: Experience with Retrieval-Augmented Generation, vector databases (Pinecone, ChromaDB, Weaviate), and semantic search
Open-Source LLMs: Familiarity with models like LLaMA, Mistral, or Phi and tools like Hugging Face
Multi-Agent Systems: Experience designing systems where multiple agents collaborate or hand off tasks
Backend Development: Experience with FastAPI or Flask for building agent-serving APIs
Cloud Platforms: Basic AWS/GCP/Azure knowledge for deploying agent workloads
Containerization: Familiarity with Docker for packaging and deploying services
Databases: Working knowledge of SQL/NoSQL and vector stores
Evaluation & Observability: Exposure to LLM evaluation tools like LangSmith or Weights & Biases
GitHub Presence: Personal projects or contributions to open-source AI/agent tooling
Who Should Apply
– You have built or experimented with AI agents, chatbots, or LLM-powered tools, even as side projects
– You are comfortable with the ambiguity and iteration that comes with building AI systems
– You don’t just want to call APIs – you want to understand why the agent behaves the way it does
– You want to grow into someone who shapes AI features in a product, not just implement tickets
Bonus: Share a GitHub repo, demo, or write-up of an AI agent or LLM project you have built.