AI Python Sr. Developer

Seeking an experienced AI Python Sr. Developer to design, develop, deploy, and govern scalable Agentic AI solutions using Python, ADK, LLMs, multi-agent systems, GCP, Terraform, and CI/CD, while establishing architectural standards, AI governance, observability, and enterprise-grade AI application delivery.

Responsibilities
AI Agent Development (40%) Design, develop, and maintain AI agents and AI-powered applications using Python and ADK. Develop reusable agent frameworks, orchestration workflows, and integrations. Build intelligent workflows leveraging LLMs, RAG, tool calling, and multi-agent systems.
Ensure reliability, scalability, observability, and performance of AI agents. Cloud Deployment & Operations (25%) Deploy, monitor, and optimize AI applications and agents on Google Cloud Platform. Manage cloud-native services, APIs, compute resources, and AI infrastructure. Implement monitoring, logging, security, and operational best practices. Optimize infrastructure and application performance for cost and efficiency.
Collaboration & Integration (15%) Partner with data scientists, analysts, architects, and business stakeholders.
Translate business requirements into AI-enabled technical solutions. Integrate AI agents into existing enterprise applications and workflows. Participate in solution design, architecture reviews, and stakeholder discussions. Infrastructure Automation (10%) Develop Infrastructure as Code (IaC) solutions using Terraform. Automate environment provisioning, deployments, and cloud configurations.
Implement CI/CD pipelines supporting AI application lifecycles. Quality Engineering & Continuous Improvement (5%) Perform unit testing, integration testing, and troubleshooting. Improve agent evaluation, observability, and operational excellence.
Resolve production issues and optimize solution performance. Other Duties (5%) Support innovation initiatives and continuous learning. Contribute to AI best practices, standards, and reusable frameworks.

Educational Qualifications: -
Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
Technical certification in multiple technologies is desirable.

Skills: -
Mandatory skills
Programming & Development Python (Expert level) Object-Oriented Programming (OOP) REST API Development Microservices Architecture Git / GitHub Agentic AI & Generative AI Agent Development Kit (ADK) Agentic AI solutions Multi-Agent Systems
Prompt Engineering LLM Integration (Gemini, OpenAI, Claude, etc.) Tool Calling and Function Calling AI Agent Orchestration Frameworks Google Cloud Platform (GCP) Vertex AI Cloud Run Cloud Functions Cloud Storage Pub/Sub BigQuery IAM Monitoring & Logging Cloud Build Infrastructure & DevOps Terraform CI/CD Pipelines Docker Kubernetes (GKE) Infrastructure as Code (IaC) Testing & Operations Unit Testing Integration
Testing Debugging & Troubleshooting Performance Optimization Monitoring & Observability L4 L7 (Tech Lead Architect Principal)
Proven experience architecting and delivering systems using agentic IDEs Ability to: Define architectural intent that agents can follow
Break features into agent executable tasks
Govern AI autonomy (guardrails, permissions, reviews) Integrate agentic workflows into CI/CD pipelines Experience supervising AI agents across:
Multi service systems Legacy modernization Large codebases / monorepos Strong understanding of: Security implications of autonomous code execution Compliance, auditability, and traceability
AI assisted SDLC operating models Core Responsibility: Guide effective use of agentic IDEs for complex, multi-module or cross-service changes Establish review practices and quality checks for AI-generated code
Mentor team members on balancing autonomy, correctness, and maintainability in AI-assisted development Design system architectures that support AI-augmented and agentic development workflows
Define guardrails, standards, and governance for the use of autonomous coding agents Evaluate impact of agentic IDEs on SDLC, CI/CD pipelines, security posture, and technical debt