• Researching, fine-tuning, and deploying state-of-the-art LLMs • Developing APIs and tools to enable seamless integration of LLM functionalities • Optimizing model performance for scalability and efficiency • Collaborating with the team to create innovative AI-driven solutions • Implementing automated checks for data quality and pipeline reliability • Supporting the integration of LLMs with Ultralytics solutions and workflows • Building internal company tools leveraging LLM capabilities • Designing and deploying Retrieval-Augmented Generation (RAG) applications • Enhancing query enrichment, reranking, and search relevance systems • Ensuring compliance with SOC 2 and ISO standards • Engaging with the open-source community to promote adoption and gather feedback • Writing and maintaining technical documentation and guides • Staying at the forefront of LLM advancements and sharing insights with the team

Intellectsoft is a software development company delivering innovative solutions since 2007. We operate across North America, Latin America, the Nordic region, the UK, and Europe. We specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive innovation and scalability. Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, and many more where our teams are making daily impact. Together, our team delivers solutions that make a difference. Learn more at https://www.intellectsoft.net/ You will be instrumental in building an enterprise-grade Agentic Framework designed to automate complex production lifecycles in heavy industries like aerospace and manufacturing. This role is for engineers who thrive in "high-unknown" environments and can move from architecture design to production-grade implementation with minimal oversight. We value candidates who leverage heavy AI code assistance to accelerate delivery without sacrificing quality

Intellectsoft is a software development company delivering innovative solutions since 2007. We operate across North America, Latin America, the Nordic region, the UK, and Europe. We specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive innovation and scalability. Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, and many more where our teams are making daily impact. Together, our team delivers solutions that make a difference. Learn more at https://www.intellectsoft.net/ You will be instrumental in building an enterprise-grade Agentic Framework designed to automate complex production lifecycles in heavy industries like aerospace and manufacturing. This role is for engineers who thrive in "high-unknown" environments and can move from architecture design to production-grade implementation with minimal oversight. We value candidates who leverage heavy AI code assistance to accelerate delivery without sacrificing quality

Role Description We're building AI-powered products, primarily leveraging off-the-shelf LLM APIs, while also partnering with our Applied Science teams to integrate custom models when needed. You'll own end-to-end development of AI features — from prototyping to production — focused on reliability, accuracy, and scalable delivery. Qualifications - Strong Python engineering skills and experience delivering production systems - Hands-on experience building with LLM APIs (OpenAI, Anthropic, etc.) and deploying AI features end-to-end - Experience with LangChain / LangGraph — including Prompt Engineering, Token Management, and Agent creation with tool-based workflows - Experience building agentic workflows (tool use, routing, memory, safety/guardrails), ideally with MCP - Solid understanding of RAG concepts — retrieval, chunking, embeddings, re-ranking, and evaluation - Practical AWS experience, especially AWS Lambda and serverless architecture patterns - Backend engineering experience: RESTful API design, webhook integration, JWT, pytest, and observability tools like Sentry - Experience doing Git repository analysis — understanding large codebases, debugging, refactors, and code health - Comfortable working in fast-moving product environments with high ownership Requirements - NextJS and TypeScript for frontend components and integration - AWS CDK for infrastructure-as-code and deployment - Broader AWS services knowledge: S3, CloudWatch, IAM, API Gateway - Experience with NoSQL databases - Experience integrating or serving custom models (inference, model endpoints, monitoring) - Familiarity with evaluation frameworks (offline tests, human feedback loops, regression suites) - Strong software engineering fundamentals: testing, CI/CD, observability, performance What You Will Do - Plan and develop applications that include custom AI components — orchestration, evaluation, tooling, and integrations - Build intelligent agents using LLMs and the MCP framework to enable context-aware automation and decision-making - Automate internal workflows and operational processes using Python and AWS Lambda - Develop and improve RAG-based chatbots to increase response accuracy, grounding, and consistency - Collaborate with Applied Science teams to productionize custom models and connect them with product systems - Design and maintain multi-agent AI pipelines, including fallback and graceful degradation strategies for reliability Benefits - $2,000 – $4,500/month — paid in USD, bi-weekly via Deel - Fully Remote — work from anywhere in Latin America - Full-time contract with a U.S. company — 6-month initial term, full-time conversion - Paid PTO — competitive package, grows with tenure - Referral Program — earn a bonus for referring talent that gets hired - Be an early employee at a fast-growing startup with direct path to technical leadership To Apply - Please send your resume in English. - Include the following: - LinkedIn Profile URL (required) - GitHub Portfolio — show us your best work (required) - Live Project Examples — applications or tools you've built (encouraged) - Cover Letter — tell us why you're excited about this role (optional but encouraged)