{"id":4229932,"url":"https://alion.io/job/proximity-ai-development-engineer","title":"AI Development Engineer","company":{"id":6179,"name":"Proximity","domain":"proximity.tech","url":"https://alion.io/company/proximity-labs","size_band":"501-1000","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Hugging Face","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLHF","optional":false},{"name":"Self-Healing","optional":false},{"name":"SFT","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-11-13T09:23:36Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T09:23:36Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"We are looking for an AI Development Engineer who is passionate about solving complex engineering problems and using AI to improve the speed, quality, and cost efficiency of software development.\nThe role involves rethinking the traditional approach to software engineering - moving from coding and implementation-heavy workflows to solution orchestration, structured thinking, detailed specifications, system design, and validation.\nYou will work on building intelligent, agentic applications that combine AI capabilities with traditional engineering systems. The focus is on using AI effectively while ensuring that the solutions we build remain reliable, secure, scalable, maintainable, and production-ready.\nKey Responsibilities\nRequirement Clarity and Engineering Design\nDevelop a deep understanding of technical requirements and system-level design to minimise rework and reduce the risk of AI-generated errors.\nTranslate ambiguous product and business ideas into clear, structured technical specifications.\nCreate specifications that serve as a reliable source of truth for both engineering teams and AI systems.\nEngineering Excellence\nEstablish practices to minimise functional defects and operational issues caused by AI-generated code.\nIdentify and eliminate code bloat, redundant logic, dead code, and unnecessary complexity.\nEnsure AI-generated code remains understandable, maintainable, and easy for engineers to navigate.\nBuild the right documentation and engineering artefacts so that AI-generated code does not become a black box.\nIncorporate security best practices into prompts, context, and code-generation workflows.\nAgentic Applications\nBuild, maintain, and scale production systems that leverage Generative AI to transform user experiences.\nDesign and monitor agentic workflows where AI components interact with traditional microservices to solve complex business problems.\nExplore and implement ways to move from manual workflows to intelligent, agent-driven applications.\nOperational Excellence\nFocus on rigorous validation as AI accelerates development and output.\nEnsure automated outputs meet high standards of security, performance, reliability, and intended functionality.\nBuild deep observability into services and systems to identify and address production issues.\nExplore self-healing production workflows where AI can interpret logs, identify issues, and suggest real-time fixes.\nCost Efficiency\nOptimise inference costs through effective prompt engineering, model selection, tool usage, and workflow design.\nBalance model performance, token consumption, and overall business ROI.\nIdentify and reduce technical debt caused by AI-generated code and redundant implementations before they affect system performance or cloud costs.\nOrganisational Leadership and Collaboration\nWork closely with Product, Production Engineering, Security, and other stakeholders to align AI capabilities with business goals and responsible AI practices.\nEncourage a culture where engineers can experiment with new AI workflows, learn from failures, and continuously improve.\nMentor junior engineers and help drive the shift from traditional coding practices towards AI-assisted engineering and system orchestration.\nRequirements\nStrong foundations in Machine Learning and AI, including linear algebra, probability and statistics, supervised and unsupervised learning algorithms, and standard MLP/DNN architectures.\nUnderstanding of bias-variance trade-offs, model fitting and selection, hyperparameter tuning, and model performance evaluation.\n5+ years of hands-on experience and working knowledge of Generative AI foundation models and LLM building blocks, including:\nTransformers for vision and text\nTokenisation and attention mechanisms\nPrompting techniques\nSupervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) concepts\nRetrieval-Augmented Generation (RAG)\nHands-on experience with prominent ML frameworks and libraries such as PyTorch, TensorFlow, and Hugging Face.\nExperience building or working on AI applications across one or more domains, including text, vision, speech, audio, and video.\nAbility to understand complex engineering requirements and translate them into structured specifications, implementation plans, and validation workflows.\nStrong problem-solving skills and an interest in exploring how AI can improve engineering workflows and application development.\nBenefits\nBest-in-class salary: We hire strong talent and compensate accordingly.\nProximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.\nContinuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.\nHigh-impact work: Build AI-first systems and products used at scale by global clients.\n\nAbout us\nProximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media and Entertainment companies in the world! We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore. Since 2019, Proximity has created and grown high-impact, scalable products used by 370 million daily users, with a total net worth of $45.7 billion among our client companies.\nWe are Proximity - a global team of coders, designers, product managers, geeks, and experts. We solve complex problems and build cutting edge tech, at scale. Our team of Proxonauts is growing quickly, which means your impact on the company’s success will be huge. You’ll have the chance to work with experienced leaders who have built and led multiple tech, product and design teams. Here’s a quick guide to getting to know us better:\nWatch our CEO, Hardik Jagda, tell you all about Proximity.\nRead about Proximity’s values and meet some of our Proxonauts here.\nExplore our website, blog, and the design wing - Studio Proximity.\nGet behind-the-scenes with us on Instagram! 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