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💻 Remote | LatAm - WE ARE EXCLUSIVELY CONSIDERING APPLICATIONS FROM INDIVIDUALS CURRENTLY RESIDING IN LATAM.
❗️ONLY ENGLISH RESUMES WILL BE CONSIDERED
🗣️ PLEASE NOTE THAT THIS ROLE REQUIRES ENGLISH PROFICIENCY (C1-C2 LEVEL)
About Motum
Motum connects experienced developers, engineers, and technical professionals with US companies building committed, long-term tech teams. Our roles are fully remote and full-time, designed for people who want real ownership, meaningful work, and the opportunity to grow inside US-based dynamic teams.
When you join Motum , you work full-time with one company, integrate directly into their team, and build a career with long-term impact. Ready to join us?
About the Client
Our client is a fast-growing US HealthTech AI company building intelligent software that helps healthcare organizations automate complex workflows and make better use of clinical and operational data.
Its AI platform works across healthcare data, documents, internal systems, and workflows to help providers and healthcare organizations reduce manual work, surface critical information faster, and improve operational efficiency.
The company is expanding how it uses generative AI across areas such as clinical documentation, healthcare operations, data retrieval, workflow automation, and decision-support tools.
You will join a highly technical, product-driven team where AI is already part of the core product. Because the platform operates in a healthcare environment, reliability, data privacy, security, and accuracy are essential.
About the Role
We are looking for a Senior / Staff Forward Deployed Engineer who can combine strong software engineering skills with exceptional customer-facing ability.
You will work directly with healthcare customers to understand complex technical and operational problems, rapidly prototype AI-powered solutions, and then turn those prototypes into reliable production systems.
This is not a traditional implementation or solutions engineering role.
You will write production code, design technical architectures, integrate complex customer systems, troubleshoot real-world environments, and own solutions from initial discovery through deployment.
You will also serve as a technical bridge between customers and the client's Product and Engineering teams, helping translate real customer problems into scalable product capabilities.
This role is ideal for an engineer who enjoys being close to both the technology and the customer and who can move comfortably between a customer conversation, architecture discussion, prototype, and production deployment.
Responsibilities
Work directly with healthcare customers to understand their technical environments, workflows, data, and business problems
Lead technical discovery sessions with engineering, product, operations, and customer stakeholders
Build AI-powered prototypes and proof-of-concepts that demonstrate how the platform can solve real customer problems
Turn successful prototypes into reliable, production-ready applications and integrations
Design and build backend services using Python, APIs, databases, and modern cloud infrastructure
Build applications using LLMs, RAG, agents, tool calling, structured outputs, and external data sources
Integrate customer APIs, EHR-related systems, databases, data warehouses, internal services, and third-party platforms
Develop AI agents capable of interacting with APIs, databases, internal tools, and external systems
Troubleshoot complex customer environments, integration issues, model behavior, data quality problems, and production failures
Design safeguards and validation mechanisms for AI systems operating with sensitive healthcare information
Own solutions from technical discovery and architecture through implementation, testing, deployment, and iteration
Communicate technical tradeoffs clearly to both technical and non-technical customer stakeholders
Partner closely with Product and Engineering to identify recurring customer needs and influence the product roadmap
Help establish best practices for deploying, monitoring, evaluating, and improving customer-facing AI systems
Mentor engineers and contribute to architecture decisions at the Senior or Staff level
Qualifications
6+ years of professional software engineering, backend engineering, machine learning engineering, or applied AI experience Candidates being considered at the Staff level should typically have 8+ years of professional engineering experience with significant technical ownership 2+ years of hands-on experience building applications with large language models or generative AI 2+ years working in a customer-facing engineering, solutions engineering, forward deployed engineering, consulting, implementation engineering, or similar technical role Proven experience shipping software products, platforms, or major technical features into production
Advanced proficiency with Python
Strong experience with TypeScript and/or JavaScript
Hands-on experience building production applications using OpenAI, Anthropic, or comparable LLM APIs
Strong understanding of RAG architecture , embeddings, vector search, document processing, retrieval, and reranking
Experience building AI agents, tool-calling workflows, or multi-step AI systems
Strong experience designing and consuming REST APIs
Experience building backend services with frameworks such as FastAPI
Strong working knowledge of SQL and PostgreSQL
Experience integrating external APIs, databases, SaaS platforms, and customer systems
Experience with at least one vector database or vector search technology such as pgvector, Pinecone, Weaviate, or OpenSearch
Experience deploying production applications on AWS, GCP, or Azure
Proficiency with Git and Docker
Strong debugging and troubleshooting skills across distributed systems and customer environments
Proven ability to independently take a technical problem from ambiguity through architecture, implementation, and deployment
Excellent written and verbal communication skills
Ability to explain technical concepts, architecture decisions, and tradeoffs clearly to customers
Nice To Have
Experience working in HealthTech, healthcare SaaS, digital health, clinical software, healthcare operations, or medical technology
Experience integrating with EHR/EMR platforms, healthcare APIs, FHIR, HL7, or clinical data systems
Familiarity with HIPAA, healthcare data privacy, PHI, security controls, or regulated software environments
Experience with AI agents, LangGraph, MCP, LangChain, or LlamaIndex
Experience with Pinecone, Weaviate, pgvector, or OpenSearch
Experience designing agent orchestration, tool-use, memory, and state management systems
Experience building automated LLM evaluation frameworks and regression testing
Experience evaluating retrieval quality, hallucination rates, task completion, latency, and model cost
Experience with multimodal AI, OCR, document intelligence, or medical document processing
Experience with hybrid search, knowledge graphs, or advanced retrieval architectures
Familiarity with observability tools and production AI monitoring
Experience with Kubernetes, Terraform, CI/CD, or infrastructure-as-code
Previous experience working directly with US enterprise customers
Startup experience in a highly autonomous engineering environment
