Role summary

The POD Lead owns end-to-end delivery of AIsolutions on GCP for the client. They design the solution, lead a pod of threeFDEs, and are the main technical face to the client's business and ITstakeholders.

Key responsibilities

•Lead the pod team: plan sprints, assign work, review code and unblock the team

•Translate client businessproblems into technical solution designs and delivery plans

•Architect AI solutions on GCP,including GenAI, LLM and agent-based workflows

•Design voice and documentmanagement solutions: speech-to-text, text-to-speech, conversational voiceagents, document extraction and classification

•Own production quality:debugging of complex issues, root-cause analysis, monitoring and performancetuning

•Run client workshops, demos,status reviews and steering updates

•Manage scope, timelines, risksand escalations with the client and internal leadership

•Set coding, security anddocumentation standards for the pod

•Mentor and grow the Senior andJunior FDEs

Required skills

•GCP stack: deep hands-on experience withVertex AI, Cloud Run, Cloud Functions, BigQuery, Cloud Storage, Pub/Sub, IAMand 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, modelevaluation

•Voice and document management: Speech-to-Text, Text-to-Speech, Dialogflow CX or similar; Document AI, OCR anddocument workflows

•Debugging:



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

•Communication and presentability: confident with senior client stakeholders; clear written updates; strongwhiteboarding 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.

- Robust 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 Professionalcertification (Cloud Architect or Machine Learning Engineer)

•CI/CD and infrastructure ascode (Cloud Build, Terraform)

•Prior experience in aclient-facing or consulting delivery role

•Experience leading teams of 3–6engineers

📌 Lead Python with AI Engineer (Bhandup)
🏢 Algoleap Technologies
📍 Bhandup