> Markdown version of [/jobs/ext/596112-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/596112-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Blue Orange Digital - **Location:** Washington, DC, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Encodings, Communications Protocols, Information Leak Prevention, Python (Programming Language), Operational Databases, Large Language Models, Snowflake, Machine Learning Operations, Databricks - **Published:** June 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d4d5579df6d822b4 ## About the Role Do you have experience in Python?, * 5+ years building production data and ML systems in Python; 2+ years specifically on LLM-based or agentic systems * Hands-on experience with at least one major LLM orchestration framework (LangChain, LangGraph, Langflow, Databricks Agent Framework, or equivalent) * Production experience with Databricks (Unity Catalog, Delta Live Tables, MLflow) or comparable lakehouse platforms such as Snowflake with dbt * Deep knowledge of RAG architectures, vector databases, and embedding pipelines * Proven track record taking AI systems from prototype to production, including evals, monitoring, and on-call ownership * Comfortable working directly with client engineering teams as a peer and a coach, * Databricks, AWS, or Azure certifications * Experience with MCP, tool-calling protocols, or agentic protocol design * Background in security-aware AI engineering (prompt injection, data leakage, access control) * Multimodal AI experience across text, document, and image * FinOps experience optimizing model and compute spend ## Description Blue Orange Digital is scaling its AI practice and needs Senior AI Engineers to deliver production agentic and AI systems to client engagements. The work is a mix of deep, single-client transformations and portfolio-wide programs. Examples of what you could be shipping in any given quarter include: * End-to-end AI transformations for mid-market SaaS companies replacing manual, human-in-the-loop workflows with fully orchestrated agentic operations (document processing, review cycles, customer-facing copilots) * AI readiness assessments and phased implementation roadmaps across private equity and growth-equity portfolios, where a single engagement may span five to fifteen portfolio companies at varying maturity levels * Production RAG and retrieval systems for knowledge-heavy domains such as financial services, legal, compliance, and regulated public-sector workflows * Agentic tooling and MCP-based integration layers that connect LLMs to client systems of record, internal APIs, and third-party SaaS * Evals, observability, and guardrail frameworks that take client-built prototypes from notebook demos to load-tested, monitored production services * Internal AI enablement engagements - helping client engineering orgs stand up their first production agent platform, define patterns, and upskill their teams, * You will work as a senior IC inside a delivery pod - the core unit of how BOD delivers AI work. A typical pod is three to five people: * AI Architect - owns the platform and data foundations * AI Transformation Consultant - drives strategy, roadmap, change management, and executive alignment * Senior AI Engineer(s) (this role) - owns the agentic and ML implementation workstream * Additional roles as needed to scale the build * Pods operate as a cohesive unit that tackles cutting-edge AI strategy and implementation end-to-end - from discovery and architecture through shipped, measured production systems - across a rotating portfolio of interesting clients. You will own the AI engineering workstream on your pod, partner daily with the Architect and Consultant as peers, and report into the Practice Lead., * Build production-grade agentic systems on Databricks and other lakehouse platforms, including orchestration frameworks, task runners, and monitoring layers * Implement RAG pipelines, vector stores, and retrieval architectures that hold up under real-world load * Stand up evals, observability, and guardrails for client-deployed AI systems * Design and integrate MCP servers and tool-calling layers between LLMs and client systems * Lead the AI engineering workstream on a client pod, partnering with the Architect on platform decisions and the Consultant on roadmap * Coach client engineering teams on production AI patterns, including prompt management, model routing, and FinOps * Contribute to BOD's internal Edge product suite, including reference architectures and the Blueprint scan engine ## Related Videos - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [A Brief History of Data Storage](https://www.wearedevelopers.com/videos/974-a-brief-history-of-data-storage) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [From A2A to MCP: How AI’s “Brains” are Connecting to “Arms and Legs”](https://www.wearedevelopers.com/videos/1631-from-a2a-to-mcp-how-ai-s-brains-are-connecting-to-arms-and-legs) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)