Senior Applied AI Engineer

Omada Health · Remote, USA · greenhouse · fit score 32.0 · 💰 $200K–$250K

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Job description

Omada Health is on a mission to bend the curve of chronic disease. Job overview: Omada Health is a digital care provider that empowers individuals to reach their health goals through sustainable behavioral change. Exceptional software with targeted AI applications is essential for delivering effective care at a broad scale. As a Senior AI Engineer at Omada, you will lead the deployment of sophisticated AI models and applications using state-of-the-art tools and platforms. This is a critical role that combines deep technical expertise with a practical understanding of applying AI in impactful ways. <h2>About you:</h2> <ul> <li>5+ years of experience deploying AI models with demonstrated business impact. </li> <li>Proven track record of designing, deploying, and managing end-to-end AI solutions, with a particular emphasis on Generative AI, prompt engineering techniques, and fine tuning.</li> <li>Deep Expertise in utilizing tools for Generative AI interaction (OpenAI, Bedrock, Huggingface TGI, Ollama, langchain, llamaindex) </li> <li>Expertise in machine learning tools (e.g., AWS SageMaker, PyTorch, Hugging Face)</li> <li>General experience in cloud ML platforms (AWS, Azure, GCP), especially with their ML services (Sagemaker and Azure ML)</li> <li>Successful monitoring of model performance post-deployment, with an ability to link AI solutions to ta

✍️ Tailored application (cached — grounded in your resume)

62 / 100 honest fit

Daniel is a strong backend/AWS/CI-CD engineer with genuine, hands-on production experience building and shipping LLM/agentic applications (Claude Code) end-to-end, which maps well to the 'applied AI' and GenAI-tooling emphasis of this role, plus deep reliability discipline from regulated medical-device software. The honest gap: his AI work is applied GenAI/agentic app development rather than formal ML-model deployment, and the resume shows no direct experience with SageMaker, PyTorch, fine-tuning, LangChain/LlamaIndex, or model-performance monitoring that this role explicitly asks for.

Tailored resume highlights

Designed, built, and operate a suite of production Flask/Python web applications, developed rapidly using LLM/agentic tooling (Claude Code) as a core part of the engineering workflow — taking ideas to deployed, monitored production services in days.
Shipped live, public AI-augmented products behind Cloudflare tunnels (gunicorn, hardened endpoints, per-IP rate limiting, automated cron data pipelines, self-healing watchdogs) serving real organic traffic.
Implemented AWS-based solutions (Lambda, S3, DynamoDB) supporting scalable data processing and monitoring for connected devices.
Built Python automation frameworks and validation pipelines integrated into CI/CD (Jenkins), enabling reproducible, fault-tolerant deployments and accelerating feature delivery.
Led root-cause analysis of complex cross-team field issues in safety-critical, regulated software where reliability and correctness are requirements — reproducing rare defects in-house and driving resolution.

"Why this company?" (draft — personalize before sending)

I've spent the last year building and shipping roughly a dozen production apps end-to-end with Claude Code and agentic tooling, so a role centered on deploying real AI applications is where my momentum already is. My day job is safety-critical, regulated medical-device software, where reliability is a requirement rather than a nice-to-have — that same discipline is what applying AI to chronic-disease care demands. Omada pairs meaningful health outcomes with the backend, AWS, and CI/CD engineering I do daily, which is exactly the combination I want to work on next.

Cover letter (review before sending)

Dear Omada Health Team, I'm applying for the Senior Applied AI Engineer role because it sits exactly where my recent work has converged: production software and applied AI in a domain where reliability genuinely matters. Over the past year I've designed, built, and operated a suite of production Flask/Python services using LLM and agentic tooling (Claude Code) as a core part of my workflow — shipping live, public products with hardened endpoints, rate limiting, automated data pipelines, and self-healing watchdogs serving real traffic. I go from idea to monitored production service in days. That AI work rests on a solid engineering foundation. At Medtronic I build backend services and AWS-based solutions (Lambda, S3, DynamoDB), develop Python automation integrated into CI/CD, and lead root-cause analysis of complex cross-team issues in safety-critical, regulated medical-device software — where correctness is a requirement, not a feature. Omada's mission to bend the curve of chronic disease pairs meaningful outcomes with the reliability discipline I've built my career on. I'd welcome the chance to contribute. Sincerely, Daniel Maynard

ATS keywords you have but should add

Generative AIprompt engineeringLLMagentic toolingend-to-end AI solutionsAI deploymentmodel monitoringfull-stackFlaskproduction deployment

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