Lead Python with AI Engineer

Experience

6+ years

Positions

1

Reports to

Delivery / Engagement Head

Role summary

The POD Lead owns end-to-end delivery of AI solutions on GCP for the client. They design the solution, lead a pod of three FDEs, and are the main technical face to the client's business and IT stakeholders.

Key responsibilities

• Lead the pod (1 Senior FDE, 2 Junior FDEs): plan sprints, assign work, review code and unblock the team
• Translate client business problems into technical solution designs and delivery plans
• Architect AI solutions on GCP, including GenAI, LLM and agent-based workflows

Design voice and document management solutions

speech-to-text, text-to-speech, conversational voice agents, document extraction and classification

Own production quality

debugging of complex issues, root-cause analysis, monitoring and performance tuning

• Run client workshops, demos, status reviews and steering updates
• Manage scope, timelines, risks and escalations with the client and internal leadership
• Set coding, security and documentation standards for the pod
• Mentor and grow the Senior and Junior FDEs

Required skills

GCP stack

deep hands-on experience with Vertex AI, Cloud Run, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, IAM and networking basics

Python

expert level; production APIs (FastAPI or Flask), async processing, testing and packaging

AI

GenAI and LLMs (Gemini or similar), prompt design, retrieval-augmented generation (RAG), agent frameworks, model evaluation

Voice and document management

Speech-to-Text, Text-to-Speech, Dialogflow CX or similar; Document AI, OCR and document workflows

Debugging

proven track record resolving production incidents across cloud services, logs (Cloud Logging) and traces

Communication and presentability

confident with senior client stakeholders; clear written updates; strong whiteboarding and demo skills

Python & Data Structures / Algorithms (DSA)

Required Skills

• 6+ Years in Expert-level Python programming with extensive experience in designing and building scalable enterprise applications.
• Strong expertise in Object-Oriented Design, Design Patterns, Concurrency, Multi-threading, Async Programming, and Microservices Architecture.
• In-depth knowledge of advanced Data Structures including Trees, Graphs, Heaps, Tries, Hash Maps, Distributed Data Structures, and Large-Scale Data Processing techniques.
• Proven experience in designing efficient algorithms and optimizing systems for performance, scalability, and reliability.
• Strong ability to review code, establish engineering best practices, and mentor engineering teams.
• Deep understanding of computational complexity, architecture trade-offs, and software design principles.
• Experience leading technical design discussions and driving engineering excellence across AI/ML and software development teams.

Good to have

• Google Cloud Professional certification (Cloud Architect or Machine Learning Engineer)
• CI/CD and infrastructure as code (Cloud Build, Terraform)
• Prior experience in a client-facing or consulting delivery role
• Experience leading teams of 3–6 engineers