{"id":2616698,"url":"https://alion.io/job/societe-generale-lead-ai-security-engineer-aps","title":"Lead AI Security Engineer-APS","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":null},"role":"Security","role_family":"Security","seniority":"lead","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":27000,"max_usd":59000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":11},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Amazon S3","optional":false},{"name":"Anthropic","optional":false},{"name":"ASP.NET Core","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"AWS Lambda","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Chroma","optional":false},{"name":"CrewAI","optional":false},{"name":"FastAPI","optional":false},{"name":"Flask","optional":false},{"name":"Function Calling","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"OpenAI","optional":false},{"name":"pgvector","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"Qdrant","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Kernel","optional":false},{"name":"Tool Use","optional":false},{"name":"Weaviate","optional":false},{"name":"Arize Phoenix","optional":true},{"name":"C#","optional":true},{"name":"Docker","optional":true},{"name":"Fine-tuning","optional":true},{"name":"Helicone","optional":true},{"name":"JavaScript","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangSmith","optional":true},{"name":"PostgreSQL","optional":true},{"name":"RLHF","optional":true}],"status":"live","first_seen_at":"2026-10-01T00:00:00Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-16T08:33:19Z","board_verified":true,"closed_at":null,"days_open":15,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":15},"description":"Responsibilities\n\n Consultant Software Engineer / AI Application Developer\nType: Full-Time | Level: Mid to Senior (7–10 Years of Experience)\nKey Responsibilities\n1. AI Application Design & Development\n•  Design and develop AI-powered applications using LLMs (OpenAI, Anthropic, Azure OpenAI, etc.)\n•  Build and maintain RAG (Retrieval-Augmented Generation) pipelines including vector stores, chunking strategies, and embedding models\n2. Agentic Solutions & Orchestration\n•  Develop agentic solutions using frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel\n•  Implement and integrate MCP (Model Context Protocol) servers and clients for tool-enabled LLM workflows\n•  Build and expose tools, APIs, and data connectors for use within agent runtimes\n•  Work with orchestration patterns: multi-agent systems, planning loops, memory management, and tool-use\n3. Quality, Evaluation & Prompt Engineering\n•  Evaluate LLM output quality, implement guardrails, and optimize prompt engineering\n4. Full Stack Development\n•  Design and develop full stack applications spanning backend (Python / .NET) and frontend (React) layers\n5. Cloud & Production Deployment\n•  Architect and deploy solutions on cloud platforms (AWS and/or Azure)\n•  Collaborate with data engineers and backend teams to integrate AI capabilities into production systems\n________________________________________\nRequired Skills\nCore Experience\n•  7–10 years of overall software development experience\n•  1–3 years of hands-on experience working in the AI/ML domain\n•  Strong full stack development experience: Python and/or .NET on the backend, React on the frontend\nTechnical Expertise\n•  Cloud platform experience: AWS (Bedrock, Lambda, S3, etc.) and/or Azure (Azure OpenAI, Azure ML, AKS, etc.)\n•  Hands-on experience building RAG pipelines (LlamaIndex, LangChain, or custom)\n•  Experience with vector databases (Chroma, Qdrant, Weaviate, pgvector, etc.)\n•  Familiarity with MCP and tool/function calling patterns in LLM applications\n•  Experience designing agentic workflows (ReAct, plan-and-execute, multi-agent)\n•  REST API development (FastAPI / Flask / ASP.NET)\n•  Understanding of prompt engineering, context window management, and LLM evaluation\n________________________________________\nNice to Have\n•  Familiarity with observability tools for LLM apps (LangSmith, Arize, Helicone)\n•  Knowledge of fine-tuning or RLHF workflows\n•  Exposure to MCP server development (SSE / stdio transport)\n•  Containerization with Docker / Kubernetes\n•  Experience working in the cyber domain or having cyber knowledge will be an added advantage\n\n Profile required\n\n Required Skills\nCore Experience\n•  7–10 years of overall software development experience\n•  1–3 years of hands-on experience working in the AI/ML domain\n•  Strong full stack development experience: Python and/or .NET on the backend, React on the frontend\nTechnical Expertise\n•  Cloud platform experience: AWS (Bedrock, Lambda, S3, etc.) and/or Azure (Azure OpenAI, Azure ML, AKS, etc.)\n•  Hands-on experience building RAG pipelines (LlamaIndex, LangChain, or custom)\n•  Experience with vector databases (Chroma, Qdrant, Weaviate, pgvector, etc.)\n•  Familiarity with MCP and tool/function calling patterns in LLM applications\n•  Experience designing agentic workflows (ReAct, plan-and-execute, multi-agent)\n•  REST API development (FastAPI / Flask / ASP.NET)\n•  Understanding of prompt engineering, context window management, and LLM evaluation\n________________________________________\nNice to Have\n•  Familiarity with observability tools for LLM apps (LangSmith, Arize, Helicone)\n•  Knowledge of fine-tuning or RLHF workflows\n•  Exposure to MCP server development (SSE / stdio transport)\n•  Containerization with Docker / Kubernetes\n•  Experience working in the cyber domain or having cyber knowledge will be an added 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