Generative AI Engineer

We are looking for a Staff Software Engineer / Staff GenAI Engineer to lead the architecture, development, and deployment of AI-driven platforms and products. This role blends hands-on engineering, system design ownership, and client-facing consulting, requiring both deep technical expertise and strong leadership.

The core responsibilities for the job include the following:

Architecture and Engineering Leadership:

• Lead the design and development of scalable backend systems integrating Machine Learning and Generative AI models into production applications.

• Architect and deliver end-to-end GenAI solutions, including LLM-based systems, RAG pipelines, and agentic workflows from prototype to production.

• Design and build agentic AI systems with capabilities like multi-step reasoning, tool usage, memory management, and orchestration.

• Develop and scale microservices and APIs supporting AI-powered applications.

• Ensure production readiness with a focus on performance, reliability, observability, cost optimization, and security.

AI/ML and Data Systems:

• Apply core machine learning techniques (regression, classification, clustering, neural networks, probabilistic models) in solution design.

• Collaborate with data scientists to train, fine-tune, evaluate, and deploy models at scale.

• Design and manage data pipelines for structured and unstructured data.

• Own data architecture across SQL and NoSQL systems (e. g., PostgreSQL, MongoDB).

Cloud and Platform Engineering:

• Define and implement cloud-native architectures across AWS, Azure, or GCP.

• Establish containerization standards using Docker and Kubernetes.

• Build and maintain CI/CD pipelines and infrastructure using Terraform or similar IaC tools.

• Implement monitoring, logging, and alerting systems for high system reliability and observability.

Product and Platform Development:

• Lead the development of AI-powered SaaS products within internal platforms (e. g., Heka.ai ).

• Drive scalable, reusable platform components for AI use cases.

Technical Leadership and Cross-Team Impact:

• Act as a DRI (Directly Responsible Individual) for major architectural initiatives.

• Own design documentation, system blueprints, and migration strategies.

• Lead incident management, triage, and prioritization across systems.

• Mentor engineers through code reviews, pairing, and career guidance.

• Break down large initiatives into epics and MVPs, driving cross-team execution.

• Lead cross-functional initiatives (performance, APIs, security, standards).

• Represent engineering in leadership discussions on delivery, reliability, and planning.

• Contribute to hiring, including interview design and candidate evaluation.

• Support Diversity, Inclusion and Belonging initiatives and mentorship programs.

Requirements:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.

• 8+ years of software engineering experience with strong backend expertise (preferably Python).

• Proven track record of delivering AI/ML or Generative AI systems in production.

• Experience with GenAI frameworks (e. g., Lang

Chain, Google ADK, agent frameworks).

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

• Hands-on experience with Docker, Kubernetes, CI/CD, and Infrastructure-as-Code (Terraform).

• Experience with databases such as PostgreSQL and MongoDB.

• Familiarity with AI-native developer tools (e. g., Cursor, Git

Hub Copilot, Claude Code).

• Strong communication skills with experience in client-facing environments.

• Prior experience in technical leadership or mentorship is preferred.