{"id":3271155,"url":"https://alion.io/job/societe-generale-senior-software-engineer-ai-engineer","title":"Senior Software Engineer - AI Engineer","company":{"id":1760180,"name":"Société Générale","domain":"societegenerale.com","url":"https://alion.io/company/societegenerale-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career sitemap","truth_index":{"grade":"B","score":81,"open_postings":96,"ghost_share":0,"stale_share":0.979,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-10-27T05:46:45Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":41},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"CrewAI","optional":false},{"name":"DeepEval","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Function Calling","optional":false},{"name":"Hallucination","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"LLM Guardrails","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-10-26T11:45:01Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-27T07:08:02Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Responsibilities\n\n We are seeking a highly skilled Senior AI R&D Engineer to focus on the cutting-edge field of agent orchestration. This role is responsible for designing, implementing, and deploying sophisticated systems that enable AI agents to execute complex, multi-step tasks autonomously. A deep, practical understanding of Large Language Models (LLMs) and the ability to rigorously evaluate agent system performance are non-negotiable.\nWhat You Will Do\nAgent Orchestration Development: Design and build advanced orchestration layers, including planning, memory management, tool-use logic, and iterative reasoning loops for autonomous agents. \nProduction Deployment: Lead the deployment of LLM-powered features and agent systems into production environments, ensuring scalability, latency targets, and reliability. \nMandatory Evaluation Mastery: Own the definition, implementation, and analysis of agent and LLM evaluation benchmarks (reference tests, heuristics, model-graded evaluation). This includes metrics for helpfulness, accuracy, hallucination, and safety. \nFramework Implementation: Leverage and contribute to modern agentic frameworks (e.g., LangChain, AutoGen, CrewAI, custom internal frameworks) to build out capabilities. \nResearch to Production: Translate the latest advancements in LLM and agent research into robust, production-ready features, collaborating closely with research scientists. \nA/B Testing: Design and execute rigorous A/B tests on prompts, system settings, and model versions, making data-driven recommendations for rollouts or rollbacks. \n\n Profile required\n\n 4+ years of professional experience in machine learning engineering, NLP, or AI R&D. \nMastery of LLM/Agent Evaluation: Demonstrated expertise in setting up, running, and analyzing evaluation systems for LLMs and agentic workflows. \nProduction Experience (Mandatory): Extensive, hands-on experience putting LLMs and at least one major agentic framework (or equivalent custom architecture) into high-volume production. \nStrong software engineering foundation, primarily in Python, with experience writing clean, maintainable, and efficient code. \nExperience in the advanced mechanisms and libraries around python, pytorch, langchain, llama index, deepeval, scikit learn. \nDeep understanding of LLM mechanisms (prompt engineering, fine-tuning, RAG, function/tool calling). \nExperience with observability tools (logging, tracing, monitoring) for real-time model performance diagnostics. \nBonus Points\nBackground in academic research (publications) related to AI, NLP, or reinforcement learning. \nExperience optimizing inference pipelines for performance and cost. \nFamiliarity with safety and guardrail systems for generative 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