AI/ML Solution Architect

Job Title: AI/ML Architect

Experience Level: 8+ years
Location: [Pune/Bangalore/Hybrid]
Type: Full-Time

Job Summary

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization.

You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value.

Roles & Responsibilities

1. Technical Leadership
• Lead the technical design and architecture of complex Generative AI systems.
• Ensure solutions align with business objectives, scalability requirements, and technical feasibility.
• Guide development teams through best practices, architecture reviews, and technical decision-making processes.
2. Solution Architecture
• Design and develop end-to-end Generative AI solutions, including data pipelines, model training, deployment, and real-time monitoring.
• Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments.
• Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks.
3. Production Deployment
• Lead the deployment of Generative AI models into production environments.
• Optimize deployment pipelines leveraging tools like Docker, Kubernetes, and cloud-native services for orchestration.
• Ensure seamless integration of GenAI solutions into existing CI/CD pipelines.
4. Data Processing & Feature Engineering
• Build scalable ETL workflows for managing structured, semi-structured, and unstructured data.
• Implement data wrangling, preprocessing, and feature engineering pipelines to prepare data for Generative AI applications.
• Optimize workflows to extract meaningful insights from large datasets.
5. Model Optimization
• Identify and implement optimization strategies such as hyperparameter tuning, feature engineering, and model selection for performance enhancement.
• Focus on computational efficiency and scaling models to production-level performance.
6. Containerization & CI/CD
• Architect and implement solutions leveraging containerization tools like Docker and orchestration platforms like Kubernetes.
• Set up or integrate into existing CI/CD pipelines to ensure seamless deployment and version control of Generative AI solutions.
7. Pilot/POCs Development
• Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements.
• Collaborate with delivery and product teams to scale successful pilots to production-grade solutions.
8. Evangelization
• Promote and drive the adoption of Generative AI solutions across customer and delivery teams.
• Provide technical leadership and mentorship to teams working on GenAI projects.
• Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders.
9. Continuous Improvement
• Stay at the forefront of AI advancements, frameworks, and tools, including emerging concepts in Generative AI.
• Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications.

Required Skills & Qualifications

• 8+ years of experience in AI/ML architecture, model development, and production deployment
• Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions
• Hands-on experience building AI agents and orchestrating agentic workflows, with the ability to deliver production-ready code
• Hands-on experience with frameworks like LangChain, Retrieval-Augmented Generation (RAG), Crew AI, and advanced prompting techniques
• Proficiency in Embeddings, Chain-of-Thought (CoT) prompting, Model Context Protocol (MCP), and Agent-to-Agent (A2A) orchestration
• Experience working with cloud platformsGCP (Vertex AI, Matching Engine), and optionally AWS (Bedrock, SageMaker) or Azure (OpenAI Service)
• Strong understanding of MLOps tools, pipelines, and model monitoring in production (e.g., MLflow, DVC, Kubeflow, LangSmith)
• Proficiency in Python and SQL for model development and data processing
• Experience with data preprocessing, ETL workflows, and feature engineering for both structured and unstructured data
• Solid knowledge of containerization (Docker) and orchestration platforms (Kubernetes, Cloud Run)
• Deep experience with CI/CD pipelines (e.g., GitHub Actions, Cloud Build) for continuous integration and deployment of AI solutions
• Proven track record of working with large datasets and optimizing models for performance and cost (e.g., hyperparameter tuning, quantization, distillation)
• Demonstrated ability to lead POCs/pilots and scale them into production-grade deployments

Preferred Skills

• Familiarity with Reinforcement Learning from Human Feedback (RLHF).
• Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks.
• Strong understanding of orchestration for large-scale production environments.

Key Attributes

• Strong technical leadership and mentorship abilities.
• Hands-on experience building AI agents and orchestrating agentic workflows.
• Excellent communication and stakeholder management skills.
• Strategic thinking with the ability to architect scalable and future-ready AI systems.
• Passion for solving business challenges using state-of-the-art AI techniques.
• Commitment to staying updated with the latest advancements in AI/ML technologies.

Why Join Us?

• Lead the development of cutting-edge Generative AI solutions for real-world applications.
• Be part of a collaborative, innovative, and technology-driven team.
• Opportunity to work with advanced AI/ML tools and frameworks.
• Drive innovation through technical leadership, mentorship, and solution evangelization.
• Continuous professional growth with access to the latest AI/ML technologies and frameworks.