{"id":2460097,"url":"https://alion.io/job/deutsche-telekom-digital-labs-senior-software-engineer-ai-2","title":"Senior Software Engineer - AI","company":{"id":409,"name":"Deutsche Telekom Digital Labs","domain":"dtdl.in","url":"https://alion.io/company/deutsche-telekom-digital-labs","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","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":["Gurgaon, 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Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false}],"status":"live","first_seen_at":"2026-10-13T17:11:40Z","employer_posted_date":null,"last_verified_at":"2026-10-13T17:11:40Z","board_verified":false,"closed_at":null,"days_open":20,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":20},"description":"Responsibilities:\nDesign and ship AI-powered product features (LLMs, RAG, agents, ML APIs) into our existing services, working closely with backend, frontend, and data science teams.\nIntegrate off-the-shelf and in-house models (LLMs, embeddings, ML APIs) into robust microservices and user-facing flows.\nDesign and implement RAG and workflow/agent pipelines: retrieval, context assembly, tools integration, guardrails, and fallbacks.\nOwn AI service reliability in production: latency, throughput, cost, observability, circuitbreakers, and rollback/versioning of models and prompts.\nCollaborate with Data Scientists who own model training/finetuning and evaluation design; productionize their outputs as stable APIs/workflows.\nImplement logging, feedback capture, and lightweight online evaluation hooks to measure the quality of AI features over time.\nEnsure safety, security, and compliance for AI features: prompt injection defenses, PII handling, abuse/hallucination controls, and audit trails.\nContribute to internal AI tooling: SDKs, templates, and reusable components to accelerate future AI use cases.\nRequirements:\nSkills required: AI Engineer role demands more than AI-based augmentation with in-depth understanding of concepts like- -RAG -GenAI, LLM finetuning, Prompt engineering, Multi-Agent framework (langchain, langraph etc with hands on experience), Eval generation and their importance, Tokens usage and optimisations, Model/mcp gateway.\nStrong software engineering in Python (and one of Node/Java/Go), REST/gRPC APIs, queues, and microservices on cloud infrastructure.\nHands-on experience shipping at least one AI powered product to production (e. g., search, recommendations, chatbots, summarization, classification).\nPractical knowledge of LLM concepts: prompts, context engineering, embeddings, vector search, basic evaluation metrics, and latency/cost trade-offs.\nSolid understanding of integration patterns with third-party AI providers (OpenAI, Anthropic, etc. ) and vector DB.\nHands-on and good understanding of at least one agentic framework like Langgraph.","description_format":"text","description_chars":2083,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Mobile Networks","IT Consulting & Digital 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