Note: The job is a remote job and is open to candidates in USA. Metas Solutions is hiring an AI Engineer to define and deliver mission-critical AI-enabled web applications for complex client challenges. The role builds generative AI applications, retrieval-based assistants, chatbots, and agentic workflows, and collaborates with architecture, engineering, product, and DevSecOps teams to deliver secure, scalable production solutions.
Responsibilities
- Build and enhance production generative AI applications and web-based AI solutions
- Develop AI applications using Azure AI Foundry, Azure OpenAI, and Foundry Agent Service
- Build retrieval-augmented generation (RAG) systems, knowledge assistants, chatbots, and agentic workflows
- Implement agent and LLM workflows that use tools, structured outputs, guardrails, and human review where needed
- Integrate AI applications with APIs, enterprise data sources, databases, cloud services, and MCP-based tools
- Develop secure, cloud-native application services and user interfaces using Python, web frameworks, containers, and Azure services
- Test, evaluate, and monitor AI applications to improve quality, reliability, latency, and cost
- Work with AI engineers, software engineers, architects, and DevSecOps teams to deliver maintainable production applications
Skills
- 5+ years of hands-on technical experience in software engineering, web application development, data engineering, data science, machine learning, or related technical discipline
- 1+ years of hands-on experience building generative AI or agentic AI solutions, including LLM APIs, prompt engineering, tool/function calling, structured outputs, retrieval-augmented generation (RAG), agents, or similar techniques
- Experience developing applications with Python and working with APIs, backend services, data pipelines, and web application frameworks
- Experience with REST APIs, JSON-based interfaces, authentication mechanisms, and external service integrations
- Experience with at least one major cloud platform, such as Microsoft Azure or AWS, including deploying or integrating applications with cloud-hosted services
- Experience using modern software-development practices and collaboration tools, such as Git, GitHub, Jira, pull requests, code reviews, issue tracking, and Agile/Scrum delivery practices
- Knowledge of LLM application fundamentals, including tokens, context windows, system and user prompts, model parameters, structured outputs, embeddings, retrieval, and techniques for guiding and evaluating model responses
- Ability to obtain and maintain a Public Trust or suitability determination, as required by the client or contract
- Bachelor's degree in computer science, engineering, or a related field
- Must be a U.S. Citizen or Lawful Permanent Resident (Green Card Holder)
- Must be US Citizen and with the ability to obtain a US Government security clearance (Public Trust 5) within a reasonable period
- Experience with containerized or cloud-native application development, including Docker, Azure Container Apps, Azure App Service, or similar services
- Experience with Model Context Protocol (MCP) integrations and agent tool calling, including hands-on development of multi-agent systems
- Experience with implementing LLM evaluation, tracing, monitoring, and observability capabilities
- Experience with CI/CD, automated testing, and cloud-based development and deployment practices for AI applications
- Experience working in government, healthcare, or other regulated environments
- Exposure to fine-tuning, hosting, or serving open-source LLMs and working with model-serving frameworks
- Knowledge of AI governance, responsible AI principles, and related security and risk-management practices
- Knowledge of AI agent frameworks such as Microsoft Agent Framework, LangGraph, PydanticAI, or similar tools
- Ability to work effectively in a cross-functional engineering environment and collaborate with software, AI/ML, data, cloud, and DevSecOps engineers
- Ability to clearly communicate technical problems, implementation decisions, and trade-offs to both technical and non-technical stakeholders
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Long and Short Term Disability
- Paid Time Off (PTO)
- Holidays
- 401K and Matching
- Growth and promotion opportunities
Company Overview