Role Summary We are looking for a Senior FullStack Engineer, AI to own and evolve Delta Exchange's suite of AI-powered products. You will work across multiple production AI applications: conversational support agents, RAG-powered search, code-generation copilots, and trading-strategy assistants. This is a hands-on role where you architect solutions around our existing stack, build retrieval pipelines, improve frontends with product sense, optimise inference costs, and run evaluations, collaborating closely with the product team. Key Responsibilities - Design, build, and maintain production AI applications end-to-end: backend, frontend, and inference services. - Architect RAG systems using vector databases, embedding models, and chunking strategies optimised for accuracy and latency. - Build agentic workflows with tool/function calling, multi-step reasoning, and structured output parsing, with accuracy and control as priority. - Write and iterate on system prompts, few-shot examples, and prompt chains to maximise output quality. - Implement function calling, tool-use patterns, and structured JSON/XML output handling using frontier and lightweight models from providers like Anthropic and OpenAI. - Drive cost optimisation: model selection, caching, token budgeting, and request batching at scale. - Build and maintain evaluation frameworks to measure accuracy, relevance, hallucination rates, and regression across prompt and model changes. Experience with observability tools (Sentry, Opik, etc.) is a must. - Work with message queues (RabbitMQ), caching layers (Redis), and relational databases (PostgreSQL) powering AI service backends. - Deploy and manage AI services on Kubernetes with CI/CD pipelines on AWS/GCP. - Integrate AI capabilities with third-party platforms (Telegram bots, chat widgets, etc.). - Contribute to architectural decisions: model selection, hosting (cloud APIs vs. self-hosted), and build-vs-buy trade-offs. Required Skills & Experience - 5+ years shipping production software systems. - 2 years building AI/LLM-powered applications end-to-end with real users and volume. Not prototypes. - Strong experience with RAG architectures: vector databases, embedding models, chunking/indexing strategies, and retrieval evaluation. - Deep understanding of LLM capabilities and limitations: prompt engineering, function/tool calling, structured outputs, context window management, and multi-turn conversations. - Experience with LLM provider APIs and abstraction layers (OpenAI, Anthropic, LiteLLM, OpenRouter, or similar). - Proficiency in Python (Flask/FastAPI) and/or Node.js/TypeScript (Next.js, Vercel AI SDK). Golang experience is a plus. - Hands-on experience building evals, tracking quality metrics, and debugging non-deterministic outputs in production. - Familiarity with cost optimisation: model routing, caching, token usage monitoring, and prompt compression. - Solid fundamentals in data structures, algorithms, and system design. - Experience with containerised deployments (Docker, Kubernetes) and cloud platforms (AWS/GCP). Practical understanding of k8s concepts and trade-offs is a must. Nice to Have - Experience with agentic frameworks (Vercel AI SDK, LangChain, Mastra, etc.). Even better if you have built Gen AI apps using raw HTTP calls to provider APIs and designed efficient conversation persistence to a database. - Background in fine-tuning or training open-source models. Huge plus if you can demonstrate matching proprietary model quality (Sonnet 4.6, Haiku 4.5, etc.) with fine-tuned alternatives. - Knowledge of cryptocurrency, derivatives trading, or financial systems. Helps understand how AI can improve product UX. - Open-source contributions or personal projects with real traction. Even a tool you built to solve your own problem counts. - Your day is spent mostly in AI coding harnesses (Claude Code, Codex, Droid, etc.), MCP servers, custom skills, and similar tooling. We use AI to build AI, and candidates already living this workflow will ramp up fast. - Proven ability to debug production AI systems: diagnosing tool call failures, optimising function calling patterns, refining prompts and tool descriptions under real traffic. - Extreme ownership and bias towards action. You treat production AI systems as your own, proactively improving quality, latency, and cost without waiting to be asked. You deliver your best work especially when no one is watching.

Role Description What You'll Do: - Conduct code reviews across the platform codebase. You will review pull requests thoroughly, provide clear and constructive feedback, and help maintain code quality standards. - Build and maintain integrations with enterprise systems including SharePoint (via Microsoft Graph API), GitLab, EPDM, and internal Hub services. - Develop and maintain LLM API integrations across multiple providers. - Build and maintain RAG pipelines: document ingestion, parsing, chunking, embedding generation, vector database storage, and retrieval. - Develop backend APIs in Python, including asynchronous request handling and background job processing. - Contribute to agent framework development. - Implement and maintain authentication and authorization flows. - Troubleshoot and fix production issues. - Collaborate with team on deployment, monitoring, and infrastructure needs. - Mentor junior engineers through code review, pairing, and technical guidance. Qualifications - Requires a Bachelor’s degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field. - 5+ years of job-related experience, or a Master's degree plus 3 years of job-related experience. - Agile experience preferred. - Due to the nature of work performed within our facilities, U.S. citizenship is required. Requirements - Expert Python skills — you need to be an expert writing, reading, and reviewing Python. - Experience building and consuming REST APIs. - Working experience with at least one major LLM API — token management, streaming responses, prompt construction, error handling. - Understanding of RAG patterns — embeddings, vector databases, document chunking and retrieval. - Experience with async programming or task queue systems. - Proficiency with Git and Docker usage. - Demonstrated ability to conduct thorough, constructive code reviews. Benefits - An exciting career path with opportunities for continuous learning and development. - Flexible schedules with every other Friday off work, if desired (9/80 schedule). - Competitive benefits, including 401k matching, flex time off, paid parental leave, healthcare benefits, health & wellness programs, employee resource and social groups, and more. Company Description General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!

Texas Sports Academy is on the lookout for a Senior AI Engineer specializing in LLM (Large Language Model) Systems and RAG (Retrieval-Augmented Generation) Optimization. As we continue to push the boundaries of sports technology, your role will be pivotal in developing and optimizing AI-driven solutions that enhance our offerings for athletes and coaches. You will be responsible for designing, developing, and fine-tuning LLM systems that can offer personalized insights and performance recommendations based on data-driven analysis. Your expertise in retrieval-augmented generation will enable the integration of comprehensive data sources, empowering our systems to deliver high-quality, context-aware content and responses. You will work collaboratively with data scientists, software engineers, and domain experts to implement scalable AI solutions that drive innovation in our training programs. If you are passionate about harnessing the power of AI to transform the sports industry and have a strong foundation in NLP and machine learning, this is the perfect opportunity for you to make an impact. Responsibilities - Design and implement LLM systems tailored to the needs of athletes and coaches. - Optimize retrieval-augmented generation processes to improve the quality and relevance of AI-generated content. - Collaborate with cross-functional teams to define AI strategies and ensure alignment with business goals. - Conduct research on cutting-edge AI methodologies and integrate them into existing systems. - Monitor and evaluate system performance, making data-driven adjustments as necessary. - Mentor junior team members and help cultivate a culture of innovation within the department. - Document system architecture, processes, and best practices for future reference and team knowledge sharing.

Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. The Data Scaling team owns the Data Flywheel for AV Foundation model development and successive fine tuning. It defines the composition of the data that is needed for the AV to learn behaviors at scale and deliver the driving behaviors necessary for the product success. The team owns the definition and processes for data quality across the data loop. The team directly works on and delivers ML models to the product that successively go up the Data Scaling curves, thereby directly impacting AV product performance through smart use of data. As part of this work, the team builds scalable systems and pipelines that attempt to 10x the data used, its diversity and impact on the models with successive major releases. The team uses existing very large datasets that GM has access to internally as well as defines the next generation of highest value datasets that GM continues to collect - both from real driving by GM and retail fleets, but also synthetic sim-based datasets. Why Join Us? - Scale up AV foundation model pre-training and fine-tuning with data to its maximum capacity - into billions+ of examples - across different sources, delivering the maximum value to the model through every additional example. - Work with cutting-edge technology and a collaborative, high-impact team of AI/ML engineers, data scientists and engineers who are passionate about leveraging advanced AI techniques to drive innovation for L2, L3 and L4 applications. - Contribute to the safety, reliability, and scalability of next-generation autonomous vehicles. As a Senior AI/ML Engineer in the Embodied AI Data Foundations organization, you will develop and deploy machine learning solutions maximally leveraging multiple sources of data including real and synthetic datasets, directly impacting autonomous driving performance. You will contribute to designing and improving ML models that go up the data scaling curves and when deployed, support safe and reliable vehicle behavior across real-world scenarios. You will collaborate closely with senior engineers and cross-functional teams to translate research and technical concepts into production-ready solutions while contributing to engineering best practices and delivery execution. What You'll Do - Develop and improve ML solutions aligned with GM's autonomous driving objectives. - Apply techniques such as unsupervised pre-training, imitation learning, reinforcement learning, model scaling/selection, foundation modeling, to solve problems in object detection/tracking/classification, trajectory generation, and safe AI. - Collaborate with cross-functional teams to deploy models into onboard driving systems. - Implement and evaluate models, incorporating research advancements into practical applications. - Contribute to taking ML solutions from experimentation through deployment and production support. - Participate in code reviews, documentation, and technical discussions to support engineering quality and knowledge sharing. Your Skills & Abilities - Bachelor's or Master's degree in Computer Science, Robotics, Machine Learning, or related field. - Experience applying machine learning techniques to real-world systems or large-scale datasets. - Proficiency in PyTorch and Python. - Experience working with model training pipelines or large-scale data processing workflows. - Strong data processing skills using tools such as NumPy, Pandas, and Apache Spark. - Ability to collaborate effectively within cross-functional engineering teams. - Experience deploying ML models into production or working within production ML environments preferred. Remote/Hybrid: This role is categorized as fully remote or hybrid. Compensation : The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area. - The salary range for this role is $159,300.00 to $230,700.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. - Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: - GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. This job may be eligible for relocation benefits. #LI-CX1 #GM-AV-1 About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Total Rewards | Benefits Overview From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us [email protected] or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.