Lead AI Engineer

Job Description

Location: Ahmedabad, India

Employment Type: Full-time

Reporting To: Head of AI & Data Science

Experience: 5 to 9 years

Role Summary: A hands-on AI engineering leader who can own client-facing AI solutioning, manage and mentor a growing engineering team, and personally deliver production-grade systems across LLMs, multi-agent applications, voice AI, computer vision, backend orchestration, and analytics.

About the Role

MSBC Group is looking for a hands-on Lead AI Engineer to lead the design, delivery, and scaling of production-grade AI systems across client and internal products. This role is intended for someone who is equally comfortable writing code, shaping architecture, guiding engineers, and speaking directly with clients.

You will lead a team of 5 to 6 engineers initially, with scope to grow the function significantly over time. At the same time, you will remain deeply involved in technical execution across applied AI use cases such as LLM applications, multi-agent systems, voice AI workflows, computer vision solutions, backend services, and analytics.

The ideal candidate combines strong technical depth with strong ownership. They should be able to take an ambiguous business problem, break it down into a practical AI solution, align internal teams, speak confidently with clients, and drive execution from discovery through deployment.

Key Responsibilities

• Lead the end-to-end delivery of AI solutions from discovery and technical scoping through development, testing, deployment, and iteration.
• Manage and mentor an initial team of 5 to 6 engineers, while building strong delivery practices, code quality standards, and engineering culture.
• Remain hands-on in engineering, architecture, code reviews, and technical problem solving across AI and backend systems.
• Design and deliver production-ready applications across LLM and RAG systems, multi-agent workflows, voice AI pipelines, computer vision workflows, and analytics-driven capabilities.
• Architect scalable backend services and APIs using Python.
• Own solution architecture for client-qualified opportunities after sales handoff, including discovery calls, solution design, technical scoping, and demo presentations.
• Translate business problems into practical AI solutions with clear delivery plans, trade-offs, and implementation paths.
• Establish best practices across testing, deployment, monitoring, performance optimization, observability, security, and maintainability.
• Work closely with product, business, and leadership stakeholders to align technical execution with business goals and timelines.
• Drive delivery discipline across projects, including technical planning, delegation, estimation, risk management, and stakeholder communication.

Required Experience

• 6 to 9 years of experience across software engineering, machine learning, or applied AI roles.
• Proven experience leading engineering teams while remaining hands-on in implementation.
• Proven experience delivering production AI projects, not only proofs of concept or research experiments.
• Strong experience in client-facing technical roles, including discovery, solutioning, and technical presentations.

Must-Have Technical Skills

• Strong programming skills in Python.
• Strong backend engineering fundamentals with FastAPI, API design, async workflows, and service orchestration.
• Strong understanding of supervised learning, unsupervised learning, model evaluation, and practical ML problem solving.
• Strong experience with LLMs, prompt engineering, RAG systems, agentic workflows, and LLM application architecture.
• Strong experience with fine-tuning and model adaptation strategies.
• Strong experience delivering computer vision systems in production environments.
• Strong experience with voice AI workflows, including speech-to-text and text-to-speech systems.
• Strong understanding of production architecture, deployment, monitoring, logging, debugging, and reliability.
• Strong analytical and problem-solving ability, with the ability to design solutions that are practical, scalable, and aligned to business needs.
• Strong understanding of data pipelines, experimentation, and AI system performance measurement.
• Experience working with cloud infrastructure and production deployments.
• Strong understanding of engineering quality, security, access control, and maintainability patterns.

Leadership and Client-Facing Expectations

• Ability to lead, mentor, and review the work of engineers across multiple parallel projects.
• Ability to run technical discovery calls after sales qualification and translate client needs into clear technical scopes.
• Ability to explain AI systems, technical constraints, trade-offs, and delivery approaches in clear business language.
• Ability to identify risks early, challenge assumptions constructively, and propose sound technical alternatives.
• Confidence presenting demos, walkthroughs, and solution narratives to client and internal stakeholders.

What We Are Looking For

• Strong ownership mindset and a bias toward execution.
• Comfort operating in ambiguity and building structure where needed.
• A highly hands-on leader who can balance speed, quality, scalability, and business value.
• A strong communicator who works effectively with clients, engineers, product teams, and leadership.
• A practical applied AI mindset focused on real-world outcomes rather than research for its own sake.

Nice to Have

• Experience with AWS-based AI deployments and cloud-native scaling patterns.
• Experience with vector databases, retrieval pipelines, and multi-step orchestration.
• Experience with MLOps, evaluation frameworks, and AI observability tooling.
• Experience working on conversational AI products, workflow automation, or customer-facing AI platforms.
• Experience building reusable internal AI platforms or AI infrastructure components.
• Familiarity with analytics dashboards, instrumentation, and AI usage insights.
• Experience in fast-moving consulting, services, or product-led delivery environments.

Why Join MSBC Group

This is an opportunity to play a leading role in building and scaling real-world AI systems across multiple business use cases. The role offers the chance to define technical direction, build strong teams, work directly with clients, and deliver AI solutions that move beyond proof of concept into production.