iFlow is hiring AI Engineer
Job Description AI Platform Engineer
Location: Pune | Hybrid
Experience: 4-6 years (mindset over tenure)
Primary Skill: Python | Secondary: .Net, TypeScript
Our Objective
We are building an AI-first engineering organization. This means embedding AI across every stage of how we design, build, test, and ship software not as a feature add-on, but as a fundamental shift in how engineering works.
You will join our central AI Centre of Excellence (CoE) and translate the AI-first vision into production-ready integrations, internal tools, and agentic workflows across our SDLC.
Key Responsibilities Workflow Auditing & AI Opportunity Mapping
- Audit existing SDLC workflows planning, development, code review, testing, and deployment to identify high-ROI AI integration opportunities
- Produce prioritised findings and recommendations for the AI CoE and engineering leadership
- Build a repeatable AI audit framework applicable across engineering teams
Hands-on AI Utility Development
- Design and develop internal tools, scripts, and LLM-powered integrations using Python
- Containerize and deploy workloads using Docker to support long-running workflows and agentic orchestrations
- Maintain a shared internal library of reusable AI components
Agentic AI Development
- Build and deploy autonomous and multi-agent AI workflows using frameworks such as LangGraph, LangChain, AutoGen, or similar
- Apply spec-driven development by defining task specifications and validating AI outputs systematically
- Integrate agentic workflows into CI/CD pipelines (GitHub, Azure DevOps, GitLab)
LLMOps & AgentOps
- Manage the operational lifecycle of LLM integrations including prompt versioning, output monitoring, cost tracking, and model updates
- Ensure agent observability by tracing sessions, monitoring tool usage, and documenting runbooks
- Define and enforce AI quality checkpoints within CI/CD pipelines
AI Evaluations & Guardrails
- Design and implement guardrails for AI-generated outputs in collaboration with the CoE team
- Run AI evaluations to measure quality, reliability, and safety
- Act as the engineering authority on hallucination detection, edge cases, and AI quality standards
AI-First Engineering Practice
- Adopt AI coding assistants such as GitHub Copilot and Cursor as daily productivity tools
- Conduct lightweight enablement sessions to upskill engineering teams
- Demonstrate high-performance AI-augmented engineering practices
Required Qualifications
- 4-6 years of hands-on software development experience (mindset and learning velocity prioritized)
- Robust SDLC fundamentals with experience applying AI across the development lifecycle
- Proficiency in Python; familiarity with .Net or TypeScript is a plus
- Hands-on experience with LLM APIs (OpenAI, Azure OpenAI, Anthropic, or equivalent)
- Practical prompt engineering experience including structured outputs and prompt versioning
- Exposure to agentic AI frameworks such as LangGraph, LangChain, AutoGen, or CrewAI
- Familiarity with LLMOps and AgentOps practices
- Practical knowledge of AI evaluations and guardrail design
- DevOps awareness including CI/CD, Docker, and enterprise Git workflows
- Hands-on use of AI coding assistants like GitHub Copilot or Cursor
Good to Have
- Experience building internal AI-powered developer tools
- Exposure to AI observability platforms such as LangSmith, AgentOps, Arize, Helicone, or Braintrust
- Prior experience in AI CoE, platform engineering, or internal developer tooling
- Exposure to Azure AI Foundry, Azure AI Search, or Azure Document Intelligence
Technology Stack
Toolchain: GitHub Azure DevOps GitLab GitHub Copilot Cursor
Cloud: Any CSP (Azure preferred)
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
📌 AI Platform Engineer (Pune)
🏢 Iflow
📍 Pune