Software Gigs

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions. Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers. Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.

Build the foundational agentic AI layer for a materials-science platform, including multi-model provider abstraction, agent orchestration with stateful checkpoints, retrieval systems, prompt versioning, and comprehensive tracing and evaluation frameworks. You'll design agents that plan and reason over tool calls in production, implement human-in-the-loop safety gates, and ensure all LLM behavior remains auditable and cost-tracked across customers' secure environments. The role demands deep production experience with agentic and LLM systems: async Python, structured outputs, memory and context management, multi-step workflow orchestration, and evaluation harnesses that catch regressions before deployment.

This is a senior-level IT support role handling escalated complex technical issues across remote and onsite client environments. The Client Engineer will troubleshoot and resolve infrastructure-layer problems spanning M365 administration (Exchange, SharePoint, Teams, Entra ID), macOS support, networking (DNS, DHCP, VPN, firewalls), and generative AI platforms, while traveling to client sites in the metro area as needed. The role requires strong technical depth, independent judgment, excellent client-facing communication skills, and the ability to quickly assess scope and determine whether issues require remote or onsite resolution. A valid driver's license and comfort working in ambiguous situations across both remote and field settings are essential.

Junior AI Software Developer supporting Navy cybersecurity and mission operations in San Diego. You will participate in problem discovery with mission stakeholders, contribute to technical solution design, and deliver hands-on implementation of scripts, APIs, automation, and AI/LLM-enabled workflows. Work involves integrating systems via REST/HTTP APIs, writing and testing Python code, using version control, and documenting technical solutions for both technical and non-technical audiences while adhering to RMF, security controls, and responsible AI practices in classified or controlled environments.

Senior AI Software Developer who will design, implement, and integrate AI/LLM-enabled solutions and automation for Navy cybersecurity and mission workflows. You'll work in small, multidisciplinary teams translating mission requirements into technical approaches, delivering hands-on code (Python, APIs, data integration), and ensuring solutions align with RMF, security controls, and compliance boundaries. The role blends advisory conversations with focused implementation of secure, deployable systems that reduce cyber risk and improve operational efficiency. Success requires 4+ years of software development or integration experience, Python proficiency, API and data store expertise, cloud or enterprise deployment knowledge, and ability to communicate across technical and non-technical stakeholders.

An AI Software Developer at Booz Allen Hamilton will design, implement, and integrate AI-enabled automation and analytics solutions for Navy cybersecurity and mission workflows. The role requires hands-on Python development, API integration, and secure system design in classified or controlled environments, with close collaboration between cybersecurity specialists, engineers, and mission stakeholders. Success demands translating mission requirements into technical tasks, delivering credible implementations (not slide-only recommendations), and operating within RMF, compliance, and secure engineering practices. The ideal candidate combines software engineering rigor (version control, code review, testing) with AI/LLM experience and the ability to work in small, structured teams on multidisciplinary problem-solving.

Senior Applied AI Engineer at West Health will design, build, and deploy production-quality AI-powered tools and workflows using large language models, multi-agent architectures, and orchestration platforms. The role involves building intelligent automation pipelines with tools like n8n, LangChain/LangGraph, and Microsoft Copilot Studio, integrating AI capabilities with existing data infrastructure (Snowflake, Python), and conducting data analysis to identify high-impact AI opportunities. The ideal candidate combines deep practical expertise in applied AI with the ability to rapidly move from concept to fully working, well-documented applications that create measurable value for healthcare delivery and senior care initiatives.

Staff Software Developer who will design, develop, and maintain AI-enabled knowledge management and decision-support platforms for environmental and engineering applications. Responsibilities include building data ingestion workflows, implementing retrieval-augmented generation (RAG) systems with vector embeddings and semantic search, developing backend services and APIs, creating secure web-based UIs, and working with cloud services (Azure AI Search, Blob Storage, PostgreSQL). The role requires strong software development skills demonstrated through a public code portfolio, familiarity with LLMs and prompt engineering, and the ability to collaborate across technical teams to translate project needs into practical features.