Engineer

• Strong hands-on experience in Machine Learning, Artificial Intelligence, and Generative AI development.
• Proven experience implementing AI/ML solutions in production environments.
• Hands-on experience working with Large Language Models (LLMs) and Generative AI applications.
• Experience developing agentic AI solutions and multi-step AI workflows.
• Strong programming skills in Python, including development of APIs, services, and ML/AI pipelines.

• Retrieval-Augmented Generation (RAG)
• Prompt engineering
• Tool/function calling
• AI agents
• Model orchestration
• Embeddings and vector search
• LLM evaluation and monitoring

• Exposure to frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, Hugging Face, or similar.
• Experience working with REST APIs, microservices, data pipelines, and enterprise integration patterns.
• Understanding of MLOps/LLMOps, CI/CD pipelines, automated testing, version control, deployment, and model monitoring.
• Experience with Git, Docker, Kubernetes, Jenkins, GitHub Actions, Azure DevOps, or comparable SDLC technologies.
• Knowledge of cloud-based AI/ML platforms such as Microsoft Azure/Azure AI, AWS/SageMaker/Bedrock, or Google Cloud/Vertex AI.
• Experience designing AI/ML solutions within model governance, model risk management, security, privacy, and regulatory frameworks.
• Strong analytical and troubleshooting skills for supporting models and AI applications in production.
• Strong communication and stakeholder-management skills, with the ability to work directly with internal clients to collect requirements and translate them into technical solutions.
• Experience supporting release planning, implementation, production deployments, and post-release activities.

• Design, develop, orchestrate, and implement production-grade Machine Learning and Generative AI solutions.
• Build applications and services leveraging LLMs, Generative AI, Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
• Develop and integrate AI agents and workflows using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent technologies.
• Evaluate and integrate foundation models and enterprise AI platforms based on business, security, performance, and governance requirements.
• Implement SDLC tooling and engineering harnesses to improve developer productivity, testing, deployment consistency, and overall team efficiency.
• Partner with internal clients and business stakeholders to elicit, analyze, and translate requirements into technical designs and implementation plans.
• Communicate technical requirements, solution designs, dependencies, and delivery expectations across engineering and business teams.
• Develop model pipelines covering data preparation, model integration, orchestration, testing, evaluation, deployment, monitoring, and ongoing support.
• Design solutions with model governance, responsible AI, risk management, security, auditability, and regulatory compliance incorporated throughout the development lifecycle.
• Support AI/ML models and services deployed within production applications, including troubleshooting, performance monitoring, and continuous improvement.
• Establish appropriate LL M evaluation and monitoring mechanisms, including model quality, hallucination risk, latency, reliability, and operational performance.
• Participate in release planning, release coordination, deployment activities, and hands-on production support during release windows.
• Collaborate with engineering, architecture, infrastructure, security, data, risk, and governance teams to ensure solutions meet enterprise standards.
• Maintain technical documentation covering solution architecture, model behavior, dependencies, deployment procedures, testing, and operational support.

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

Qualifications

BACHELOR OF COMPUTER SCIENCE