{"id":1452479,"url":"https://alion.io/job/rarr-technologies-senior-aiml-engineer","title":"Senior AI/ML Engineer","company":{"id":3801593,"name":"RARR Technologies","domain":"rarrtech.com","url":"https://alion.io/company/rarr-technologies","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":22000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":28},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"PoC Library","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"AWS","optional":true},{"name":"GCP","optional":true},{"name":"JavaScript","optional":true},{"name":"Machine Learning","optional":true},{"name":"Next.js","optional":true},{"name":"OpenAI","optional":true},{"name":"React.js","optional":true}],"status":"live","first_seen_at":"2026-09-29T06:38:02Z","employer_posted_date":null,"last_verified_at":"2026-09-29T06:38:02Z","board_verified":false,"closed_at":null,"days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"Role Overview : \n\nWe are looking for an experienced Senior AI/ML Engineer with strong hands-on expertise in Generative AI, Agentic AI, LLMs, RAG, AI evaluation, cloud-native engineering, and solution architecture. The role will involve designing, developing, evaluating, and deploying production-grade AI solutions while working closely with business and technical stakeholders to translate complex and ambiguous requirements into scalable, secure, and reliable solutions.\n\nKey Responsibilities : \n\n- Design, develop, and deploy production-grade AI/ML and Generative AI solutions for complex business use cases.\n\n- Build and integrate LLM-powered applications, AI agents, copilots, intelligent automation, and agentic workflows.\n\n- Design and implement scalable RAG pipelines, including data ingestion, chunking, embeddings, retrieval, context management, and response generation.\n\n- Develop and optimize prompt engineering, orchestration, tool/function calling, and agent workflows.\n\n- Design and implement AI evaluation frameworks, including evaluation datasets, scoring methodologies, rubrics, agent-performance testing, and failure-mode analysis.\n\n- Establish mechanisms to measure and improve accuracy, relevance, reliability, safety, latency, and overall AI solution performance.\n\n- Design scalable, resilient, and secure cloud-native AI architectures using modern distributed systems and microservices principles.\n\n- Develop and manage Infrastructure as Code (IaC) for AI solutions and cloud environments, particularly on Microsoft Azure.\n\n- Build and maintain APIs, services, data integrations, and supporting components required for enterprise AI applications.\n\n- Translate business and technical requirements into solution architectures, system designs, technical specifications, and implementation plans.\n\n- Lead technical discovery sessions with clients and stakeholders to understand business problems, identify AI opportunities, and define practical solution approaches.\n\n- Take AI solutions from prototype/PoC through production deployment, monitoring, optimization, and support.\n\n- Collaborate with Data Engineering, Product, Architecture, Cloud, Security, and business teams to deliver end-to-end solutions.\n\n- Conduct technical design reviews and code reviews and promote reusable engineering patterns and best practices.\n\n- Troubleshoot complex issues across AI applications, APIs, data pipelines, cloud infrastructure, and distributed systems.\n\n- Optimize AI workloads for scalability, performance, reliability, latency, and cost.\n\n- Mentor engineers and contribute to team capability development in modern AI/ML and cloud technologies.\n\n- Stay current with advancements in LLMs, Agentic AI, AI evaluation, AI engineering practices, and Azure AI services.\n\nRequired Skills & Experience : \n\n- 5 - 10 years of experience in software engineering, AI/ML engineering, or related technology roles.\n\n- Strong hands-on experience with Python or an equivalent programming language.\n\n- Proven experience building and deploying AI/ML solutions in production environments.\n\n- Strong understanding of LLMs, Generative AI, prompt engineering, and model deployment.\n\n- Hands-on experience with Agentic AI, AI agents, LLM workflows, copilots, or intelligent automation.\n\n- Strong experience designing and implementing RAG-based solutions.\n\n- Hands-on experience with AI/LLM evaluation, including evaluation datasets, scoring/rubrics, model or agent testing, and failure analysis.\n\n- Strong understanding of distributed systems, microservices, APIs, and cloud-native architecture.\n\n- Hands-on experience with Infrastructure as Code (IaC) in cloud environments, particularly Azure.\n\n- Experience with modern AI/ML frameworks, APIs, and enterprise data-integration patterns.\n\n- Strong solution architecture and system design capabilities.\n\n- Advanced understanding of the AI Development Lifecycle (AI-DLC) and production AI engineering practices.\n\n- Experience designing secure, scalable, and maintainable AI solutions.\n\n- Proven experience participating in or leading client discovery, solution design, and technical delivery.\n\n- Strong stakeholder-management skills across technical, business, and executive audiences.\n\n- Excellent communication, presentation, problem-solving, and storytelling skills.\n\n- Ability to structure ambiguous business and technical problems into actionable solution approaches.\n\n- Strong ownership mindset with the ability to independently drive AI initiatives from concept to production.\n\nPreferred / Good to Have : \n\n- Master's degree in AI/ML, Data Science, Computer Science, Software Engineering, or a related discipline.\n\n- Experience with React / Next.js for AI-enabled user interfaces.\n\n- Knowledge of healthcare data, regulatory requirements, interoperability, or healthcare technology.\n\n- Experience with Adobe Experience Platform (AEP) or enterprise Marketing Technology platforms.\n\n- Exposure to LLM observability, AI governance, responsible AI, and model monitoring.\n\n- Experience with major AI/cloud platforms such as Azure OpenAI, AWS, or GCP.\n\nSkills\nGenerative 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