{"id":2769483,"url":"https://alion.io/job/epergnesolutions-principal-engineer-ai","title":"Principal Engineer AI","company":{"id":3909615,"name":"Epergnesolutions","domain":"epergnesolutions.com","url":"https://alion.io/company/epergnesolutions","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":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":62000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":44},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false}],"status":"live","first_seen_at":"2026-10-06T20:56:29Z","employer_posted_date":null,"last_verified_at":"2026-10-06T20:56:29Z","board_verified":false,"closed_at":null,"days_open":16,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":16},"description":"Job Role:- Principal Engineer AI\n\nJob Location:- Bengaluru, India\n\nExperience:- 10-15 Years\n\nRole Summary:-We are seeking a Principal Engineer AI Research to lead the architecture, design, and delivery of production-grade AI platforms and agentic AI systems. This is a hands-on technical leadership role focused on building scalable, secure, and high-performance AI infrastructure that enables the deployment of advanced Generative AI, multimodal AI, and autonomous AI solutions across on-premise and cloud environments.\nKey Responsibilities:-Design and implement end-to-end architectures for agentic AI systems, Generative AI platforms, RAG pipelines, and AI inference workflows.\nBuild scalable AI platforms supporting distributed training, model deployment, and enterprise integration.\nOptimise system performance, latency, throughput, GPU utilisation, and infrastructure costs.\nLead debugging, production incident resolution, performance tuning, and reliability improvements.\nDevelop reusable AI frameworks, SDKs, APIs, connectors, and CI/CD templates.\nImplement observability, monitoring, logging, tracing, and operational dashboards.\nEstablish engineering standards, architecture governance, testing frameworks, and controlled release processes.\nCollaborate with research, product, data, and platform teams to translate AI research into production-ready systems.\nMentor engineering teams and drive best practices in software engineering, MLOps, and AI platform development.\nRequired Skills:-Strong expertise in AI system architecture, distributed systems, cloud platforms, and scalable backend engineering.\nExperience with Generative AI, LLM deployment, RAG systems, agentic AI frameworks, and AI orchestration platforms.\nProficiency in Python and modern software engineering practices.\nExperience with MLOps/LLMOps, containerisation, Kubernetes, CI/CD, monitoring, and infrastructure automation.\nKnowledge of distributed training, GPU optimisation, vector databases, and real-time inference systems.\nStrong debugging, performance optimisation, and reliability engineering skills.\nExcellent technical leadership, collaboration, and mentoring abilities.\nQualifications & Experience:-Bachelors, Masters, or PhD in Computer Science, Artificial Intelligence, Software Engineering, or a related field.\n1015 years of experience in software engineering, AI platforms, machine learning infrastructure, or distributed systems.\nProven experience designing and delivering large-scale production systems and AI platforms.\nExperience leading technical architecture, engineering standards, and cross-functional delivery initiatives.\nPreferred Attributes:-Hands-on principal-level engineering expertise.\nStrong understanding of security, governance, observability, and production operations.\nExperience building reusable engineering platforms and developer tooling.\nAbility to translate advanced AI research into reliable enterprise-grade 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