Role & responsibilities

About the Role

We are hiring an AI Engineering Manager to lead a team of full-stack AI engineers delivering GenAI-powered agents and applications built on React and Python (FastAPI). You will own technical architecture and delivery, grow and manage the team, and partner with product and business stakeholders to set direction for automation across HR, Payroll, SAP, and Client Delivery. This is a hands-on leadership role you will still review designs and guide complex technical decisions, but your primary leverage is through your team.

Key Responsibilities

- Lead, mentor, and grow a team of full-stack AI engineers; own hiring, onboarding, performance management, and career development
- Own the technical architecture for agent platforms spanning React front-ends, Python/FastAPI services, and LLM orchestration layers
- Drive delivery planning, prioritization, estimation, and execution across multiple workstreams
- Set and uphold engineering standards for code quality, testing, security, observability, and deployment
- Partner with Product Managers, SMEs, and business leaders to shape the roadmap and turn business processes into an agentic automation strategy
- Make build-vs-buy and framework decisions (LangChain, LangGraph, CrewAI, etc.) and guide RAG, multi-agent, and integration patterns
- Ensure scalable, secure, and reliable systems integrating with enterprise platforms (Workday, SAP, Salesforce)
- Remove blockers, manage technical risk and debt, and report progress and outcomes to leadership
- Stay hands-on enough to review architecture and code and to guide the hardest technical decisions

Lead the design and development of full stack AI-integrated applications and

microservices.

- Oversee the implementation of agentic workflows, including agent-to-agent

interactions and AI API integrations.





- Manage cloud-native and on-prem deployments, including local LLM setups

(HuggingFace, Ollama).

- Develop and optimize RAG platforms, focusing on vector databases, embeddings,

retrieval, prompting, and evaluation.

- Ensure observability, telemetry, and optimization of AI applications.
- Implement CI/CD pipelines, containerization, and orchestration using Docker,

Kubernetes, and serverless platforms (Azure Functions, AWS Lambda).

- Design and manage event-driven architectures using Azure Service Bus, RabbitMQ,

and Kafka.

- Ensure best practices for RESTful API design, security, and documentation.
- Collaborate with engineering, data science, and machine learning teams to drive

project success.

- Make architecture decisions, execute roadmaps, and maintain quality standards.

Qualifications

- Bachelors or Masters degree in Computer Science, Software Engineering, or a related field
- 12 + years in software/AI engineering, including 4+ years leading or managing engineering teams
- Proven delivery of production full-stack systems (React + Python) and AI/ML or GenAI solutions
- Robust architectural judgment across front-end, back-end, and LLM/agent orchestration
- Deep familiarity with agentic frameworks (LangChain, LangGraph, CrewAI, ReAct) and LLM orchestration
- Experience with enterprise integrations, distributed systems, cloud (Azure / AWS / GCP), containers/Kubernetes, and security best practices
- A track record of hiring, mentoring, and growing high-performing engineering teams
- Excellent stakeholder management and communication skills
- Nice to Have

- Experience scaling GenAI / agent platforms in production
- Background in enterprise-scale business process or workflow automation
- Open-source leadership or active community contributions
- Experience defining MLOps / LLMOps and observability practices

📌 Artificial Intelligence Engineer - Senior Manager (Telangana)
🏢 PwC
📍 Telangana