Senior Python Engineer (Tech Lead) – AI Agent Systems (7+ Years)

We are looking for a highly skilled Senior Python Engineer to lead the design and delivery of cutting-edge AI agent systems. This is a hands-on role for someone who thrives in ambiguity, can independently run critical projects, and takes full ownership from architecture to deployment.

You will build and deliver real-world agent use cases such as smart home automation agents, coding copilots, or creative design assistants — collaborating directly with clients and leading teams to success.

Key Responsibilities

• Lead and deliver end-to-end Python-based solutions for intelligent agent systems.
• Architect, design, and implement critical components yourself — not just manage.
• Collaborate with cross-functional teams and clients to scope, refine, and deploy solutions.
• Act as a single point of ownership for high-priority initiatives.
• Mentor and guide team members to achieve technical excellence.

Must-Have Skills

• 7+ years of experience in Python development with end-to-end solution delivery.
• Strong design and architecture skills, with the ability to work independently.
• Excellent coding standards, debugging skills, and code review practices.
• Clear communication skills and ability to work in fast-paced, high-context environments.

Candidates should have strong hands-on experience with most of the following:

Core Python:

• Advanced Python programming (OOP, async, multithreading, multiprocessing)
• Design patterns and clean architecture

AI/ML & Agents:

• LLM & AI frameworks: LangChain, LlamaIndex, Haystack
• ML/DL frameworks: PyTorch, TensorFlow, scikit-learn
• NLP libraries: spaCy, NLTK, Hugging Face Transformers
• Model serving: FastAPI, Flask, Ray Serve
• Prompt engineering & evaluation tooling

Data & Storage:

• pandas, NumPy for data manipulation
• Vector databases: FAISS, Pinecone, Weaviate
• SQLAlchemy, PostgreSQL/MySQL connectors
• Data pipeline tools: Prefect, Airflow

System & Deployment:

• FastAPI/Flask for APIs
• Docker, Kubernetes, Terraform for deployments
• Logging, testing, and observability: pytest, pydantic, OpenTelemetry

Nice-to-Have Skills

• Experience with real-world IoT or automation protocols (MQTT, Home Assistant APIs)
• Familiarity with reinforcement learning or fine-tuning LLMs
• Knowledge of JavaScript/React for building agent interfaces

Vetting Process

• Profile Screening: Two rounds of profile review based on resume.
• Technical Interviews: Two rounds of delivery-focused interviews for shortlisted candidates.

Perks:

• Fully remote engagement.
• Opportunity to work on cutting-edge AI projects with leading LLM companies.
• Ownership of impactful, end-to-end agent use cases.