Lead AI/ML Engineer - Full Stack Development

About This Role

The Lead AI/ML Engineer is a strategic technical leader responsible for designing, building, and deploying advanced AI/ML solutions across the full application stack. This role drives innovation and scalable AI adoption within the organization.

Responsibilities

• Architect, develop, and deploy scalable AI/ML platforms and full stack application solutions, spanning model training, inference, APIs, and user experiences
• Implement AI/ML computing infrastructures and application stacks using frameworks such as AWS Bedrock core/Google ADK, with orchestration using AWS AgentCore for multi agent workflows
• Design end to end pipelines covering data ingestion, feature processing, model serving, and observability
• Build and maintain production grade backend services and APIs using Java and Python
• Develop and integrate frontend and lightweight UI components (e.g., dashboards, internal tools) to operationalize AI workflows and analytics
• Apply modern software engineering practices including CI/CD pipelines, containerization, and cloud native deployment
• Partner closely with data scientists, product managers, UX teams, and business stakeholders to translate complex business requirements into scalable AI and full stack solutions
• Lead technical design reviews, guide architectural decisions, and oversee model evaluation, optimization, and deployment cycles
• Mentor junior and senior engineers, setting clear expectations for code quality, system design, and operational readiness
• Conduct applied research to advance capabilities in Generative AI, NLP, NLU, computer vision, and predictive modeling

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field
• 9+ years of professional software engineering experience, with demonstrated success designing and delivering high quality, commercial full stack applications in production environments
• 6+ years of hands on proficiency in Java, Python, SQL, and Linux shell scripting, with production experience in distributed systems
• 5+ years of AI/ML engineering experience, including deploying models at scale and leading or mentoring technical teams
• 4+ years of Strong cloud experience in various CSPs ( especially AWS)
• 2+ years of applied AI/ML experience, including deep learning, NLP/NLU, semantic understanding, intent classification, ASR, predictive modeling, and time series analysis
• 2+ years of experience in MongoDB and MLOps

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field
• 9+ years of professional software engineering experience, with 6+ years hands-on proficiency in Java, Python, SQL, and Linux shell scripting, and 5+ years of AI/ML engineering experience

Nice to Have

• Proven cloud experience with Google Cloud (Vertex AI) and working knowledge of AWS, including cloud native architectures, containerization, and orchestration
• Hands on experience with Hadoop ecosystems, and MLOps practices for model lifecycle management
• Experience integrating AI/ML models into end to end, user facing applications
• Solid understanding of API based architectures, distributed data systems, and scalable backend services
• Experience working in enterprise or regulated environments with governance and compliance requirements
• Proven ability to clearly present complex analytical and AI concepts to both technical and non technical audiences
• Solid grounding in statistics, probability theory, optimization, simulation, and data modeling

Skills

* Required skills

Benefits