AI/ML Engineer

Primary Responsibilities:

- Design, develop, and deploy AI-powered solutions, digital workers, and intelligent automation capabilities that drive measurable business outcomes and operational efficiency.

- Rapidly prototype, validate, and scale emerging AI technologies (Generative AI, Agentic AI, automation, orchestration, and analytics) to address enterprise transformation opportunities.

- Partner with business, architecture, engineering, and operations teams to identify high-value use cases and translate them into production-ready AI solutions.

- Establish and promote AI engineering best practices, reusable frameworks, governance standards, and responsible AI controls to accelerate enterprise adoption.

- Evaluate disruptive technologies, drive innovation pilots, and build strategic capabilities that position the organization for future-state digital operations.

Required Qualifications:

- Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related technical discipline.

- 5+ years of experience in software engineering. Proven track record developing APIs, microservices, cloud-native architectures, CI/CD pipelines, DevSecOps, and observability.

- 3+ years of experience building solutions on a Python stack. Hands-on experience with core AI capabilities, such as generative AI, agentic AI, LLMs, vector databases, embeddings, semantic search, and knowledge retrieval.

- 5+ years working on teams using agile and lean coding methodologies, such as pair or mob programming.

Essential Skills

• 3+ years of experience building solutions on a Python stack. Hands-on experience with core AI capabilities, such as generative AI, agentic AI, LLMs, vector databases, embeddings, semantic search, and knowledge retrieval.
• 5+ years working on teams using agile and lean coding methodologies, such as pair or mob programming.
• Experience integrating AI solutions with enterprise platforms, business workflows, data platforms, and operational systems to deliver measurable business outcomes.
• Strong communication skills for cross-functional collaboration and stakeholder interactions.

Desired Qualifications

• Familiarity with MLOps tools and workflows for monitoring prediction accuracy, detecting feature drift, and assessing ongoing model fit and/or degradation.
• Structured AI/GenAI training with a capstone project and practical solution development experience.