Head of AI Engineering

Comviva Technology; Pune District, Gurugram District, Bengaluru; On-site; INR 2,500,000 - 5,000,000; Full time

Job summary

Comviva Technology seeks a senior AI Engineering Lead in Pune to steer an AI team delivering agents, copilots, and automation across enterprise products. You’ll own delivery lifecycle from planning to production readiness, partnering with product, architecture, and business stakeholders to translate AI use cases into executable roadmaps.

You will guide best practices, drive DevOps and CI/CD for AI platforms, and mentor engineers to scale capabilities while maintaining security and governance

Qualifications

• Bachelor’s degree in Computer Science, IT, AI, Data Science, or related field.
• 12+ years of software engineering experience, with 3–5 years leading teams in product development.

Responsibilities

• Lead the AI Engineering team building AI agents, copilots, and intelligent automation.
• Own end-to-end delivery for AI initiatives, including planning, execution, quality, release readiness, and operability.
• Collaborate with product, architecture, and business stakeholders to translate AI use cases into executable plans.
• Build and scale a high-performing AI Engineering team with ownership, discipline, collaboration.
• Drive sprint planning, prioritization, estimation, dependency management, and delivery governance for AI initiatives.
• Ensure AI solutions meet scalability, performance, security, observability, and maintainability standards.
• Partner with the AI Architect to align with solution design and long-term tech direction.
• Provide technical leadership on implementation approaches, best practices, and production readiness.
• Establish development processes, coding standards, DevOps, and quality controls for AI apps.
• Collaborate with platform, DevOps, QA, security, and product teams for integration and deployment.
• Drive AI use cases such as intelligent assistants, copilots, and workflow automation.
• Monitor progress, manage risks, and ensure timely delivery of outcomes.
• Plan capacity, hiring, and performance for the AI team.
• Define metrics for productivity and quality; drive continuous improvement.
• Foster innovation, accountability, and disciplined execution in AI teams.
• Ensure compliance with security, privacy, responsible AI, and governance.
• Support production rollouts, incidents, and continuous improvement of AI capabilities.
• Stay updated on industry trends and adopt relevant AI tech aligned with goals.

Skills

Python

APIs

Microservices

Cloud

LLMs

Prompt engineering

Agile delivery

Stakeholder mgmt

Education

Bachelor's degree in CS/IT or related field

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Job description

Key Accountabilities

• Lead the AI Engineering team responsible for building AI-powered agents, copilots, and intelligent automation solutions across enterprise products and platforms.
• Own end-to-end engineering delivery for AI initiatives, including planning, execution, quality, release readiness, and operational stability.
• Work closely with product management, architecture, and business stakeholders to convert AI use cases and product goals into executable engineering plans.
• Build and scale a high-performing AI Engineering team with strong ownership, engineering discipline, collaboration, and execution focus.
• Drive sprint planning, prioritization, estimation, dependency management, and delivery governance for AI-related initiatives.
• Ensure AI solutions are developed with the required standards of scalability, performance, reliability, security, observability, and maintainability.
• Partner with the AI Architect to ensure that engineering implementation aligns with defined solution architecture, design standards, and long-term technology direction.
• Provide technical leadership to the team by guiding implementation approaches, engineering best practices, code quality, testing discipline, and production readiness.
• Establish development processes, coding standards, review mechanisms, DevOps practices, and quality controls for AI applications and platforms.
• Collaborate with platform, DevOps, QA, security, and product engineering teams to ensure smooth integration and deployment of AI capabilities into enterprise products.
• Drive execution of AI use cases such as intelligent assistants, recommendation engines, knowledge copilots, reporting assistants, support automation, and workflow intelligence solutions.
• Monitor engineering progress, identify execution risks, remove blockers, and ensure timely delivery of committed outcomes.
• Own team capacity planning, resource allocation, skill development, performance management, and hiring for the AI Engineering team.
• Define productivity, quality, and operational metrics for the team and drive continuous improvement across delivery and engineering practices.
• Foster a culture of innovation, accountability, experimentation, and disciplined execution within the AI Engineering team.
• Ensure compliance with enterprise standards related to security, privacy, responsible AI usage, access control, auditability, and governance.
• Support production rollouts, issue resolution, incident management, and continuous improvement of AI capabilities in live environments.
• Stay updated on industry trends, AI engineering practices, and emerging technologies, and drive relevant adoption in alignment with product and engineering goals.

Required Skills & Experience Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or a related field.
• 12+ years of experience in software engineering, with at least 3 to 5 years of experience leading engineering teams in product development environments.

Domain & Technical

• Relevant hands‑on experience in AI/ML, Generative AI, LLM-based applications, or intelligent automation platforms.
• Proven experience in managing engineering teams delivering enterprise-scale software products and complex technology initiatives.
• Strong programming and technical understanding in areas such as Python, backend development, APIs, microservices, distributed systems, and cloud-native applications.
• Good understanding of Large Language Models, prompt engineering, embeddings, semantic search, vector databases, retrieval‑augmented generation, and agent‑based application development.
• Strong experience in engineering delivery management, Agile execution, sprint planning, estimation, release management, and cross‑functional coordination.
• Ability to translate business and product requirements into structured engineering plans, delivery roadmaps, and execution milestones.
• Experience in building high‑performing teams through effective hiring, mentoring, coaching, and performance management.
• Strong understanding of software quality practices, code reviews, testing strategies, CI/CD pipelines, monitoring, observability, and production support models.
• Good knowledge of cloud platforms such as AWS, Azure, or GCP and modern deployment practices for enterprise applications.
• Strong stakeholder management, communication, and collaboration skills with the ability to work with product, architecture, engineering, and business teams.
• Ability to manage technical risk, delivery challenges, and operational issues in a structured and proactive manner. Knowledge of Agile methodologies and modern product engineering practices.

Desirable

• Experience in enterprise software, SaaS platforms, customer engagement platforms, analytics products, or digital transformation programs.
• Experience leading teams building AI assistants, copilots, chatbots, or agentic applications for enterprise use cases.
• Familiarity with AI orchestration and agent development frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or similar tools.
• Exposure to Java, Spring Boot, Node.js, Kafka, workflow engines, and event‑driven enterprise platforms. Familiarity with vector stores, caching layers, LLMOps tools, AI observability platforms, and model evaluation practices.
• Understanding of recommendation systems, analytics platforms, personalization engines, and decisioning systems.
• Experience driving engineering governance in areas such as secure development, privacy compliance, responsible AI, and enterprise controls.
• Experience working in collaborative and cross‑functional global product engineering teams.
• Understanding of end‑to‑end enterprise AI platform engineering and production deployment considerations.