AI Engineer

Bates White Economic Consulting is seeking an AI Engineer to design, develop, and deploy AI-driven workflows and autonomous agents using LLMs and other AI systems across the firm's enterprise AI platforms.

Key Responsibilities

• Design, build, and deploy AI workflows and agentic solutions that leverage LLMs and other AI systems, using existing enterprise AI platforms (including Azure AI Foundry, Azure OpenAI, Databricks, AWS such as Bedrock and SageMaker AI, and Google Cloud Vertex AI and Gemini), and evaluate and onboard new platforms as needs evolve.
• Develop, orchestrate, and maintain multi-step agent workflows, including tool use, function calling, retrieval-augmented generation (RAG), and integration with enterprise data sources, applications, and APIs.
• Apply a thorough understanding of LLMs and emerging AI systems, including model selection, prompt design, context management, embeddings and vector stores, and tradeoffs among inference, retrieval, and fine-tuning to choose appropriate approaches for each use case.
• Partner with business stakeholders and firm leadership to translate business requirements into production-grade AI solutions.
• Build reusable frameworks, components, and pipelines that allow the broader data engineering team to develop, test, and scale AI solutions efficiently across cloud platforms.
• Establish and apply responsible AI practices aligned with firm AI governance policies and client contractual obligations, including data privacy and security, prompt injection and abuse mitigation, and evaluation and guardrails.
• Monitor, evaluate, and continuously improve accuracy, performance, cost, and reliability of deployed AI systems, including token usage optimization.
• Build and maintain CI/CD pipelines and automated testing for AI workflows and agents, and manage model lifecycle activities such as version upgrades, deprecations, and migrations as providers release new models.
• Extend AI solutions to multi-modal use cases as needed by incorporating vision, audio, or other modalities alongside text-based LLMs.
• Stay current with the evolving AI landscape and advise the team on emerging models, tools, and techniques, including alternatives to the firm's primary Azure-based stack such as AWS and Google Cloud/Gemini.

Required Qualifications

• Bachelor’s degree in computer science, data science, engineering, or a related field (advanced degree preferred).
• Minimum 7 years’ experience in software engineering, data engineering, or a closely related technical field.
• Minimum 3 years of hands-on experience building AI solutions focused on large language models (LLMs) and agent-based systems.
• Thorough understanding of LLM architecture, capabilities, and limitations, including the ability to reason about and adopt new AI systems as they emerge.
• Proficiency in Python and modern AI/ML frameworks and libraries; familiarity with multi-modal models (vision and audio) is a plus.
• Demonstrated experience building agentic workflows, RAG pipelines, and LLM integrations using frameworks such as LangChain, LlamaIndex, Semantic Kernel, or comparable tooling.
• Experience with enterprise AI platforms including Azure AI Foundry, Azure OpenAI, or Databricks, or comparable platforms on AWS (Bedrock, SageMaker AI) or Google Cloud (Vertex AI, Gemini).
• Experience working with vector databases and embedding models.
• Proficiency in prompt engineering, model evaluation, and the use of guardrail and safety tooling.
• Proficiency working with REST APIs and integrating AI systems into enterprise applications and data pipelines.
• Familiarity with MLOps/LLMOps tooling such as MLflow, Weights & Biases, and LangSmith for experiment tracking and model monitoring.
• Familiarity with Microsoft Azure and other major cloud providers (AWS, Google Cloud); the firm is Azure-focused but open to other platforms.
• Familiarity with data privacy, security, and responsible-AI considerations for enterprise AI systems is preferred.
• Experience with SQL and working with structured and unstructured data sources is advantageous.
• Strong problem-solving and analytical skills.
• Ability to work effectively under dynamic circumstances, tight deadlines, and high-pressure situations.
• Ability to successfully work with individuals of varying backgrounds, levels, and departments.
• Excellent oral and written communication skills, including communicating complex technical and AI concepts to diverse audiences.
• May require more than 40.0 hours per week to perform the essential duties of the position.

Technologies

• Azure AI Foundry, Azure OpenAI, Databricks
• AWS: Bedrock, SageMaker AI
• Google Cloud: Vertex AI, Gemini
• Python, LLMs, RAG
• LangChain, LlamaIndex, Semantic Kernel
• Vector databases, embeddings
• CI/CD pipelines, REST APIs
• MLflow, Weights & Biases, LangSmith
• Microsoft Azure, SQL

Compensation and Benefits

• Competitive compensation: USD 160,000 to 190,000 per year; eligible for bonus compensation on a discretionary basis.
• Comprehensive benefits package: tuition reimbursement up to $75K , low healthcare premiums, wellness benefits, and more.
• Hybrid work environment: three coordinated in-office days per week.
• Culture: open culture with emphasis on your voice, input, and recognition for contributions; fun and engaging culture with frequent social events.
• Amenities: fitness center, rooftop terrace, standing desks, espresso, fresh fruit, breakfast and afternoon snack, billiards, and ping pong.
• Community outreach: employee-driven community outreach featuring fundraising events, volunteer opportunities, and matching funds along with the pro bono program.
• Career support: training programs, an assigned mentor and peer coach, and frequent feedback.
• Networking opportunities: employee interest groups, Women's Network, International Network, Diversity-Inclusion Council, and BWProud Network.

Location

Washington, DC (hybrid).