AGILE Services Group is a technology consultancy that builds production-grade AI, cloud, and platform systems for startups, growth-stage SaaS, enterprise teams — and when the mission calls for it, federal programs. Generative AI, LLMs, multi-agent systems, RAG, AWS, and Kubernetes. Fully remote across the US with on-site availability in Baltimore, Washington DC, Philadelphia, and Northern Virginia.
AGILE Services Group was founded on a simple premise: the best consulting happens when senior engineers do the work, not manage it from a distance. We build production AI systems, cloud platforms, and the infrastructure under them — for startups that need to ship fast, for growth-stage SaaS teams scaling past early product/market fit, for enterprise teams modernizing legacy stacks, and for federal programs where compliance and security can't slip.
Our practice today is AI-first: generative AI strategy, LLM integration, RAG pipelines, AI agents and multi-agent governance frameworks, and the AWS / Kubernetes platforms that run them in production. We've pioneered multi-agent engineering pipelines with role-based governance, pre-flight validation, and automatic rollback — compressing delivery timelines from months to weeks.
That depth is backed by 26+ years of shipping at every layer of the stack — cloud governance, distributed systems, security and compliance (FedRAMP, NIST 800-53, HIPAA), healthcare technology (HL7 FHIR), and proposal architecture contributing to over $50M in awarded federal contracts across NOAA, HHS, CMS, FDA, VA, and IRS. Federal credentials are one thing we bring to the table — not the whole table.
Based in Baltimore. Fully remote across the US. On-site engagements in the DMV, Philadelphia, and the broader Mid-Atlantic.
LLM products, RAG platforms, multi-agent systems, and AI infrastructure — shipped, monitored, and operating in real environments, not demos.
Cloud, platform, and AI engineering for startups, growth-stage SaaS, enterprise teams, and federal programs. Principal-engineer mentality on every engagement.
Technical proposals and solution architecture for federal agencies including NOAA, HHS, CMS, FDA, VA, and IRS — one credential among many.
No junior hand-offs. No account managers. Direct access to the engineers building your system.
Hands-on consulting for teams that need senior engineering talent — not slide decks. AI-first, private-sector first, remote-ready.
End-to-end LLM product engineering: prompt design, RAG pipelines, vector databases, tool use, evals, guardrails, and production deployment on AWS, Azure, GCP, or self-hosted. We work with OpenAI, Anthropic Claude, Google Gemini, and open-source models (Llama, Mistral) via Ollama and vLLM.
Production multi-agent architectures on LangGraph and custom frameworks — with role-based governance, pre-flight validation, and automatic rollback. Used for engineering automation, research, customer support, coding agents, and domain-specific workflows. We pioneered AI-driven self-healing test automation and multi-agent engineering pipelines that compress delivery timelines from months to weeks.
Where to apply generative AI for real business outcomes — use-case identification, build-vs-buy decisions, model selection, evaluation strategy, and 6–12 month execution roadmaps. Also available as fractional CTO, fractional AI leader, or fractional Chief Architect for startups and growth-stage companies needing senior technical leadership without a full-time hire.
Production-grade infrastructure on AWS, multi-cloud, and hybrid environments. Kubernetes platform design, cost optimization, migrations, and modernization for commercial and regulated workloads. From network topology to storage strategy, we architect systems that perform under real-world conditions.
Internal developer platforms and CI/CD pipelines that accelerate delivery. Container orchestration, GitOps, infrastructure as code, observability, and self-service tooling that lets teams move fast safely. SRE practices for teams scaling past early stage.
Build compliant, secure platforms in healthcare and benefits administration. Experience with HL7 FHIR, benefits processing systems, PHI-handling architectures, and the regulatory requirements that come with sensitive health data.
Zero-trust architecture, SSO/OIDC, IAM governance, and compliance frameworks for commercial and regulated workloads. When the mission calls for it, we bring 20+ years of experience achieving ATO for federal systems under FedRAMP, NIST 800-53, and FISMA — one credential among many, not the identity.
Architecture, AI capability, security, and team assessment for investors, acquirers, and boards — including AI claims validation. Also: architecture reviews, technology selection, and strategic guidance for engineering teams who want to make the right infrastructure decisions before investing months in the wrong direction.
A look at the kind of work we take on and the problems we solve.
Designing and building the cloud infrastructure for a healthcare benefits platform that processes sensitive member data. Our team handles API architecture, FHIR integration, database design, and ensuring the entire stack meets healthcare compliance requirements.
A high-availability Kubernetes cluster running 30+ production services — including SSO, GitOps, media infrastructure, document management, and AI workloads. This is both a production environment and a proving ground for the technologies we deploy for clients.
Tools and systems we've built and released publicly.
An AI-powered voice assistant built on local LLMs with RAG capabilities. Runs on Apple Silicon and NVIDIA Jetson edge hardware with Home Assistant integration, real-time speech processing, and multi-room audio coordination.
A codebase field guide and context layer for unfamiliar systems. SourceBridge analyzes repositories to help engineers understand complex codebases fast — architecture, conventions, and critical paths surfaced automatically.
AI-powered visual regression testing platform. Captures screenshots, compares against approved baselines using pixel-level and AI perceptual analysis (SSIM, LPIPS, DINOv2, VLM), and surfaces diffs through an approval workflow. Self-hosted — your data stays on your network.
Articles on applied AI, multi-agent systems, software architecture, and the evolving relationship between engineering teams and the AI tools they rely on.
AI writes code fast — but who catches the visual regressions? How I built a self-hosted visual testing platform to keep AI-generated changes from silently breaking the UI.
How a weekend experiment turned into a 30-service AI system that runs entirely in my home — faster, smarter, and with zero cloud dependencies.
AI isn't just helping us write code. It's changing our relationship to understanding it. And the gap between what we ship and what we comprehend is growing.
Looking back on introducing mob programming to my team, what made it work, and why AI tools might give it a second life.
How I built a four-layer infrastructure to make AI agent destruction recoverable by design — Forgejo mirrors, Harbor caching, immutable S3 backups, and automated dependency scanning.
AI coding tools make it easy to build systems nobody fully understands. Here's the six-phase engineering loop I use to keep speed without losing discipline.
Production-tested tools and platforms. Not a list of things we've read about — technologies we deploy, operate, and troubleshoot at 2 AM.
30 minutes. No sales pitch. Tell us about the AI product you're building, the platform you're scaling, or the problem you're trying to solve. Remote or on-site (Baltimore, DC, Philly, NoVA).
Whether you're shipping your first AI product, scaling a platform past early stage, evaluating a vendor's AI claims, or modernizing a regulated workload — tell us about your project. Private sector first. Federal clients welcome. Fully remote across the US; on-site in Baltimore, DC, Philadelphia, and Northern Virginia.