Staff GenAI Engineer

We are seeking a Staff Software Engineer / Staff GenAI Engineer, for Mumbai location, to provide technical leadership in the design, development, and deployment of AI-driven platforms and products. This role combines hands-on engineering expertise with architectural ownership and client-facing consulting responsibilities.

Key Responsibilities

• Lead the architecture, design, and development of scalable backend systems integrating machine learning and Generative AI models into production-grade applications.

• Drive end-to-end delivery of GenAI solutions, including LLM-based systems, RAG architectures, and agentic workflows, from experimentation to production.

• Design and implement agentic AI systems enabling multi-step reasoning, tool calling, memory management, and orchestration.

• Apply a strong understanding of machine learning techniques (regression, classification, clustering, decision trees, neural networks, probabilistic models) to solution design and implementation.

• Collaborate closely with data scientists to train, fine-tune, evaluate, and deploy ML/AI models, ensuring reliability and performance at scale.

• Work with structured and unstructured data sources, designing efficient data pipelines and storage strategies.

• Lead development of backend microservices and APIs supporting AI-driven applications.

• Ensure production readiness of AI systems, including performance optimization, monitoring, cost control, and security.

• Define cloud-native deployment strategies for AI solutions on AWS, Azure, and GCP.

• Establish containerized deployment standards using Docker and Kubernetes across development and production environments.

• Oversee data architecture, performance, and integrity across SQL and NoSQL databases (PostgreSQL, MongoDB).

• Implement monitoring and logging frameworks to ensure reliability, observability, and operational excellence of AI systems.

• Lead the development of AI-powered SaaS products within the Heka.ai platforms.

Tactical cross-team leadership

• Be a DRI for major architectural initiatives and blueprints; own design docs and migration plans.

• Maintain ownership of triage and incident prioritization; advocate severity/priority to stakeholders.

• Serve as a maintainer/owner for multiple critical repositories, tech stacks, or services.

• Mentor engineers formally; grow others via code reviews, pairing, and career coaching.

• Break down large efforts into epics and MVCs; coordinate cross-team delivery.

• Facilitate or lead working groups for cross-cutting initiatives (performance, APIs, security, standards).

• Represent your group to leadership: engineering allocation, reliability status, and iteration health.

• Participate in hiring: design interviews, assess candidates, and recommend bias-reduction improvements.

• Participate in Diversity, Inclusion Belonging initiatives and mentorship programs Qualifications

• Education: Bachelor s/masters degree in computer science, Software Engineering, or a related field.

• Experience Technical Skills :

• 8+ years of experience 8+ years of experience in software engineering, with strong backend expertise in Python and GenAI Exposure.

• Proven experience delivering AI/ML or Generative AI systems in production environments.

• Familiarity with gen Ai frameworks like Lang chain, Google ADK and other Agent development Kits.

• Strong knowledge of cloud-native architectures, microservices, and distributed systems.

• Hands-on expertise with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code (Terraform).

• Experience with PostgreSQL, MongoDB, or equivalent databases.

• AI-Native Engineering: Experience utilize Cursor, GitHub Copilot, or Claude Code as a core part of their daily workflow.

• Ability to operate in client-facing environments and communicate complex technical concepts clearly.

• Experience mentoring or leading technical teams is preferred.

Staff Engineer Traits (What Success Looks Like)

• Thinks in systems, not just features.

• Acts as a force multiplier for technical teams.

• Drives clarity in ambiguous technical situations.

• Chooses long-term maintainability over short-term hacks.

• Communicates complex ideas with precision and calm authority.

• Leads through technical credibility, not hierarchy.