AI Engineer

Position Summary:

The AI Engineer is responsible for design, build, and deploy innovative AI-powered products and productivity solutions. This role is focused on turning business ideas into real-world applications using off-the-shelf platforms, Azure/AWS components, and modern AI frameworks. This role works in close partnership with the Enterprise AI Solutions Architect, software development engineering teams, and data engineering teams to bridge the execute and implement enterprise solutions using AI technologies. The ideal candidate is a software builder, who thrives on creating scalable, user-facing solutions using the latest in GenAI, CoPilot, and enterprise AI tools. The role will play a key role in shaping how AI is used across the organization, from internal productivity enhancements to customer-facing services.

Key Responsibilities

• Collaborate with business stakeholders to translate ideas into AI-powered products and services.
• Build and deploy enterprise-ready AI solutions using LLMs, semantic search, text-to-SQL, and other GenAI capabilities.
• Implement productivity solutions using Microsoft CoPilot, Office AI tools, and other enterprise platforms.
• Rapidly prototype and iterate on AI applications using Azure, AWS, and off-the-shelf tools.
• Partner with the AI Solutions Architect to ensure scalable, secure, and compliant system design.
• Develop APIs and lightweight UIs (e.g., Streamlit, FastAPI, Snowflake Cortex) to deliver AI tools to end users.
• Stay current on emerging AI technologies, including vector databases, RAG pipelines, and productivity AI platforms.
• Drive delivery of AI components aligned with product roadmaps and business priorities.

Core Technical Environment

• Data & Cloud: Snowflake (Cortex AI), Azure, AWS, Google Cloud
• ML/AI Frameworks: TensorFlow, PyTorch, Scikit-learn, MLflow, Hugging Face
• LLMs & NLP: Llama, Mixtral, RekaCore, Snowflake (Cortex AI), LangChain, MCP
• CV: YOLOv5 for image/video object detection (as applicable)
• UI & Deployment: Streamlit, FastAPI, Flask
• Semantic Search & Text2SQL: Cortex Analyst, vector DBs (e.g., Weaviate, Qdrant)
• MLOps: GitHub Actions, CI/CD, containerization, pipeline orchestration

Qualifications:

Education

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field.

Work Experience:

• 3+ years of hands-on experience in machine learning engineering or AI solution delivery.
• Proven experience building and operationalizing models at scale using structured and unstructured data.
• Experience working with Agile (SAFe) teams, iterative delivery cycles, and DevOps practices.
• Prior success in deploying GenAI or LLM-based applications in enterprise or healthcare settings is a strong asset.
• Experience working within a clinical regulated industry, and developing CRF Part11 compliant solutions
• Experience with Microsoft 365 CoPilot, Office AI tools, or similar productivity AI platforms
  • Technical Stack and Tools:
• Cloud platforms and services (Azure, AWS)
• Data platform architecture using Snowflake
• Experience integrating knowledge graphs (e.g., Neo4j, RDF/SPARQL, AWS Neptune) into AI pipelines for semantic reasoning and structured context

Skills & Competencies

• Ability to convert experimental models into high-performing, reliable production services.
• Strong software engineering fundamentals, with a focus on model observability, testing, and automation.
• Clear communicator who can distill technical detail for non-technical stakeholders.
• Agile mindset with comfort in fast-paced, iterative environments.
• Deep appreciation for data privacy, bias mitigation, and responsible AI practices. Commitment to ethical AI development and AI governance principles.