David Altuve

Senior AI Software Engineer with 8+ years of experience building web applications, backend systems, and AI-powered software solutions. Skilled in Python, FastAPI, Django, Node.js, React, cloud platforms, databases, and modern AI tools such as OpenAI API, LangChain, RAG, and NLP. Experienced in designing scalable systems, integrating APIs, improving application performance, and deploying applications on AWS, GCP, and Azure.

Strong background working with healthcare, fintech, edtech, entertainment, and enterprise projects, with the ability to lead technical work and collaborate with cross-functional teams.

Senior AI Software Engineer at Sciencesoft (2023-09 – Present)

• Built production LLM applications using Python/FastAPI, Node.js, OpenAI API, LangChain, LangGraph, and RAG pipelines for enterprise search, document analysis, workflow automation, and AI-assisted decision support.
• Designed agentic AI workflows with routing, tool calling, memory, validation, and fallback paths where simple prompt chains were not reliable enough for production business processes.
• Integrated MCP servers, internal APIs, and external services so AI agents could retrieve data, trigger actions, validate outputs, and escalate uncertain cases to human reviewers.
• Developed RAG systems using Pinecone, PostgreSQL, and Elasticsearch, improving answer quality through better ingestion, chunking, metadata filters, hybrid search, reranking, and source traceability.
• Built knowledge graph-based retrieval with Neo4j, entity extraction, relationship modeling, and graph traversal to support more contextual answers across domain-specific datasets.
• Added LLM evaluation and guardrail checks for grounding, prompt regressions, hallucination risk, low-confidence answers, and failed tool calls before workflows reached production users.
• Deployed AI services on AWS with Docker and Kubernetes, using EC2, Lambda, S3, RDS, IAM, CloudWatch, and separate staging/production environments.
• Added observability with structured logging, Prometheus metrics, CloudWatch dashboards, and trace IDs to diagnose model latency, retrieval failures, API errors, and workflow bottlenecks.
• Built React, Next.js, TypeScript, and Tailwind interfaces for AI chat, workflow automation, analytics, admin tools, and human-in-the-loop review screens.

Senior Software Engineer at Coherent Solutions (2020-09 – 2023-08)

• Built backend platforms for edtech, entertainment, fintech, and enterprise clients using Python, FastAPI, Django, Node.js, Golang, and microservice-based architecture.
• Designed REST, GraphQL, and WebSocket APIs for real-time dashboards, collaboration features, notifications, reporting, and workflow automation.
• Improved backend reliability by fixing slow queries, duplicated background jobs, cache invalidation gaps, unclear service boundaries, and weak deployment checks.
• Designed data models and query patterns across PostgreSQL, MongoDB, Elasticsearch, ClickHouse, and Snowflake for search, reporting, analytics, and audit-heavy product features.
• Built early AI-assisted features using NLP, BERT-based classification, semantic search, and document tagging to improve content discovery and reduce manual review.
• Deployed services across AWS, GCP, and Azure using Docker, Kubernetes, CI/CD pipelines, Prometheus metrics, and environment-specific configuration.
• Expanded testing coverage with Jest, Cypress, integration tests, and API contract checks around authentication, payments, reporting, and customer workflow services.
• Partnered with frontend, QA, DevOps, and product teams to debug production issues, clarify requirements, and release backend changes without breaking dependent systems.

Software Engineer at Mercury Development (2018-06 – 2020-08)

• Built full-stack applications for healthcare, enterprise, and consumer-facing products using Python, Django, Node.js, Vue.js, AngularJS, TypeScript, and HTML5.
• Improved application performance by reducing repeated database queries, adding Redis caching, and optimizing PostgreSQL, MySQL, and MongoDB access patterns.
• Supported early AI and data-processing features using Python, NLP, search pipelines, and classification models for document analysis and content organization.
• Assisted with AWS deployments using EC2, S3, RDS, IAM, CloudWatch, Docker, and CI/CD pipelines, reducing staging release time from about 40 minutes to 15 minutes.
• Worked closely with senior engineers, QA, and product teams to clarify requirements, fix production issues, and document common support patterns.

Full Stack Developer at xCures (2017-11 – 2018-05)

• Built healthcare application features for patient intake, provider workflows, internal case tracking, and administrative review screens using Python, Django, JavaScript, and React.
• Added authentication, role-based access controls, API validation, and audit-friendly data handling for sensitive healthcare workflows.

Software Development Engineer Intern at Amazon (2016-06 – 2016-08)

• Assisted in developing internal product features using Hack/PHP, Python, JavaScript, and React within large-scale engineering environment.
• Built backend components and data-processing workflows for internal tools supporting operational analytics and user management tasks.

Bachelor's Degree in Computer Science – Tokyo University of Technology (2013 – 2017)