Generative AI Engineer

Job Description: Staff Software Engineer / Staff GenAI 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.

Key Responsibilities Architecture & 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 & 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 & 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 & 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 & 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 & Belonging initiatives and mentorship programs.

Qualifications Education

• Bachelor’s or Master’s degree in

Computer Science, Software Engineering , or related field.

Experience & Skills

• 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., LangChain, 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, GitHub Copilot, Claude Code).

• Strong communication skills with experience in

client-facing environments .

• Prior experience in

technical leadership or mentorship is preferred.

What Success Looks Like (Staff Engineer Traits)

• Thinks in

systems, not just features .

• Acts as a

force multiplier for engineering teams.

• Brings

clarity to ambiguous technical problems .

• Prioritizes

long-term scalability and maintainability .

• Communicates complex ideas with

precision and confidence .

• Leads through

technical influence, not authority .

What We Offer

• Opportunity to work on

cutting-edge AI and GenAI projects in a global environment.

• Access to

leadership development programs and advanced training .

• A

collaborative, high-impact engineering culture with diverse problem spaces.