We're hiring a Full Stack Software Engineer to build the infrastructure that powers our AI agents and ML systems end-to-end — from UX/UI, fine-tuning foundation models to shipping production-grade agent harnesses.

Role: Senior AI Engineer

Location: India (Onsite)

Experience:

8+ years of experience in Python development, including building and supporting production systems
Hands-on experience working with agent-based or agentic systems, using at least one framework such as LangGraph, CrewAI, AutoGen, LangChain, or LlamaIndex
Exposure to designing or contributing to MLOps pipelines, with familiarity with tools like Kubeflow
Practical experience in fine-tuning large language models (for example, open-source models like Llama, Mistral, Qwen, or similar)
Experience deploying containerized applications on Kubernetes, including areas like Helm, operators, networking, and resource management
Familiarity with at least one major cloud platform (AWS, GCP, or Azure), including services related to compute, storage, identity access management, and machine learning

Key Skills:

Python
ReactJS/TS
Kubeflow
MLflow
Argo
Airflow
Kubernetes
LangGraph
CrewAI
AutoGen
LlamaIndex
SOLID principles
secure coding
static analysis
code reviews
CI/CD

Qualification:

Bachelor’s or Master’s degree in Engineering

Role Focus:

Design UX and build UI for Agentic Ops
Design and build agent harnesses in Python — the runtime scaffolding that enables AI agents to perceive, reason, plan, and act reliably
Develop and maintain a robust MLOps framework using Kubeflow and complementary tooling (MLflow, Argo, Airflow, or similar) to orchestrate training, evaluation, and deployment workflows
Fine-tune foundation LLMs using techniques such as LoRA/QLoRA, SFT, and RLHF; manage datasets, training runs, and evaluation pipelines
Deploy and operate services on Kubernetes, including model serving, autoscaling, and observability
Build and integrate AI agents using modern agent frameworks (LangGraph, CrewAI, AutoGen, LlamaIndex, or similar)
Apply software engineering rigor — SOLID principles, secure coding, static analysis, code reviews, and CI/CD — across all deliverables

Nice to have:

Exposure to distributed training approaches, using tools such as DeepSpeed, FSDP, or Accelerate
Familiarity with vector databases, retrieval-augmented generation (RAG) systems, and evaluation frameworks for language models
Experience working with model serving solutions such as vLLM, TGI, KServe, or Triton

Senior AI Engineer

Skills Required

Description

Experience:

Key Skills:

Qualification:

Role Focus:

Nice to have:

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