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Roles and Responsibilities:

- Lead the design, development, and deployment of AI/ML solutions, Generative AI applications, and enterprise AI platforms.
- Architect and implement LLM-powered applications, RAG pipelines, AI agents, multi-agent systems, and intelligent copilots.
- Drive AI solution design, technology selection, proof of concepts, and production implementation aligned with business objectives.
- Lead and mentor AI/ML engineers, software developers, and data scientists, ensuring engineering quality and timely delivery.
- Design scalable backend services, APIs, microservices, and distributed systems to support AI-powered applications.
- Develop context engineering strategies, knowledge retrieval mechanisms, prompt engineering approaches, and model evaluation frameworks.
- Integrate AI capabilities with enterprise applications, databases, search platforms, workflow engines, and external services.
- Implement workflow automation and orchestration solutions, including human-in-the-loop processes where required.
- Establish best practices for AI/ML model development, deployment, versioning, monitoring, and continuous improvement using MLOps.
- Ensure AI solutions meet requirements for scalability, performance, security, reliability, responsible AI, and data privacy.
- Collaborate with product managers, architects, business stakeholders, and engineering teams to translate business requirements into effective AI solutions.
- Evaluate emerging AI technologies, LLMs, agent frameworks, and cloud AI services to identify opportunities for innovation and optimization.
- Drive CI/CD automation,



observability, cost optimization, and operational excellence across AI/ML platforms and applications.

Skillset:

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- 8+ years of experience in software engineering, AI/ML development, or technology delivery, with proven experience leading AI/ML teams and initiatives.
- Strong programming skills in Python, with familiarity with Java, Kotlin, TypeScript, JavaScript, or Go.
- Strong understanding of Machine Learning, Deep Learning, Generative AI, Large Language Models (LLMs), and model evaluation techniques.
- Hands-on experience with Retrieval-Augmented Generation (RAG), context engineering, vector databases, embeddings, and knowledge engineering.
- Experience designing and developing AI agents, multi-agent systems, agent frameworks, and AI copilots.
- Strong understanding of backend engineering, APIs, microservices, event-driven architectures, and distributed systems.
- Experience with workflow automation, orchestration platforms, and human-in-the-loop systems.
- Knowledge of relational and NoSQL databases, caching, search platforms, analytics, and lakehouse platforms.
- Experience with cloud platforms such as AWS, Azure, or GCP, along with Docker, Kubernetes, and infrastructure-as-code.
- Solid understanding of DevSecOps, CI/CD, MLOps, model deployment, monitoring, observability, and AI security.
- Excellent leadership, communication, problem-solving, and stakeholder management skills.

📌 ValueLabs - AI/ML Lead (India)
🏢 VALUELABS SOLUTIONS
📍 India