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FCI-CCM

Senior AI/ ML Engineer

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Broad Function:<\/u><\/b>
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We are looking for a Senior AI/ML Engineer<\/b> to join our AI Platform team and drive the design, development, and production deployment of intelligent agentic systems. You will work at the intersection of cutting\-edge Gen AI research and real\-world engineering, owning end\-to\-end delivery of LLM\-powered products \u2014 from RAG pipelines and multi\-agent orchestration to model fine\-tuning, safety guardrails, and observability.
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This is a hands\-on, high\-ownership role. You will mentor engineers, influence architecture decisions, and collaborate closely with product and data science teams to ship AI features that are reliable, scalable, and safe
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Purpose of the Role:<\/u><\/b>
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To design, build, and deploy scalable AI/ML solutions, including LLM\-powered and agentic systems, ensuring high performance, reliability, and safety. Drive end\-to\-end delivery of AI products while mentoring teams and influencing architecture to enable impactful, production\-ready AI capabilities.<\/span>
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Roles and Responsibilities (not limited to):<\/u><\/b>
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1.\tCore AI & Generative AI:<\/b><\/span>
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\u2022\tDesign and develop advanced AI systems including:
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\u2022\tAgentic RAG, Adaptive RAG pipelines
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\u2022\tMulti\-Agent Systems (MAS)
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\u2022\tEvaluate and optimize LLM outputs based on:
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\u2022\tRetrieval quality
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\u2022\tAnswer relevance and faithfulness
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\u2022\tBuild scalable AI workflows using frameworks such as Lang Chain and Lang Graph Testing and Support.
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2.\tModel Fine\-Tuning & Alignment:<\/b><\/span>
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\u2022\tImplement fine\-tuning techniques such as:
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\u2022\tLoRA and QLoRA
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\u2022\tEnhance model performance through alignment strategies ensuring:
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\u2022\tAccuracy
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\u2022\tSafety
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\u2022\tDomain relevance<\/span>
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3.\tAI Protocols & Integration:<\/b><\/span>
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\u2022\tWork with emerging AI standards including:
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\u2022\tModel Context Protocol (MCP)
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\u2022\tAgent\-to\-Agent (A2A) communication
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\u2022\tIntegrate AI systems into enterprise environments
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\u2022\tLeverage tools such as Agent Development Kit (ADK)
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4.\tMachine Learning & NLP:<\/b><\/span>
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\u2022\tApply strong ML fundamentals including:
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\u2022\tModel evaluation, cross\-validation, and hyperparameter tuning
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\u2022\tWork with NLP concepts such as:
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\u2022\tTokenization, embeddings, transformers, attention mechanisms
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\u2022\tDevelop models using PyTorch and/or TensorFlow
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5.\tEngineering & Production:<\/b>
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\u2022\tDevelop scalable, production\-grade applications using Python
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\u2022\tOptimize databases using SQL/PostgreSQL
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\u2022\tWork on full\-stack integrations
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6.\tData & Vector Infrastructure:<\/b>
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\u2022\tDesign and implement vector\-based architecture using pgvector, Pinecone, Weaviate, Qdrant, etc.
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\u2022\tBuild: Embedding pipelines<\/span>
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\u2022\tChunking strategies
\u2022\tScalable similarity search systems
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7.\tMLOps & Observability:<\/b>
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\u2022\tManage ML lifecycle using tools like: MLflow, Weights & Biases
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\u2022\tImplement monitoring for:
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\u2022\tModel drift
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\u2022\tAccuracy degradation
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\u2022\tData quality issues
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8.\tPrompt Engineering & LLM Safety:<\/b>
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\u2022\tDesign advanced prompting strategies: Chain of Thought (CoT), few\-shot, prompt tuning
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\u2022\tMitigate risks such as:
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\u2022\tPrompt injection
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\u2022\tAdversarial inputs

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9.\tAI Safety & Guardrails:<\/b>
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\u2022\tImplement guardrails to ensure safe and compliant AI outputs:
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\u2022\tContent filtering
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\u2022\tToxicity detection
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\u2022\tResponse boundary control
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\u2022\tCollaborate with security and compliance teams to ensure adherence to policies and regulations<\/span>
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CULTURAL TRAITS (Critical Fit Requirements):<\/u><\/b>
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  • High ownership with end\-to\-end delivery mindset in a fast\-paced environment<\/span>
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  • Strong focus on innovation and continuous learning in AI/GenAI<\/span>
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  • Effective cross\-functional collaboration across teams<\/span>
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  • Comfortable in high\-impact, stakeholder\-facing roles<\/span>
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  • Agile problem\-solver with strong accountability<\/span>
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  • Committed to secure, ethical, and responsible AI development<\/span>
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    Requirements<\/h3>
    Desired Qualifications & Experience:<\/u><\/b>
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    • 6\u20138 years of overall experience in software development.<\/span>
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    • 3\u20134 years of hands\-on experience in AI/ML roles, preferably within a product\-based organization (non\-services/consulting).<\/span>
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    • Proven track record of building and deploying AI/ML solutions from prototypes to production.<\/span>
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    • Demonstrated experience in leading and mentoring teams of 5+ engineers, including conducting code reviews, design reviews, and providing career guidance.<\/span>
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    • Strong cross\-functional collaboration skills, with the ability to effectively work with product managers, data scientists, and platform/engineering teams.<\/span>
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    • Open\-source contributions to AI/ML frameworks.<\/span>
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    • Experience with Graph RAG or Knowledge Graph\-backed retrieval.<\/span>
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    • Familiarity with ADK (Agent Development Kit) or similar low\-level agent runtimes.<\/span>
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    • Java or React exposure for full\-stack AI product integration.<\/span>
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    • Proficient in AWS and Azure for deploying and scaling AI/ML workloads.<\/span>
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    • Familiarity with managed ML services: SageMaker, Azure ML, Bedrock, or OpenAI API platforms.
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      Benefits<\/h3>
      The company offers a range of employee benefits including:<\/u><\/b>
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      • Cashless medical insurance for employees, spouses, and children<\/span>
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      • Accidental insurance coverage<\/span>
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      • Life insurance coverage<\/span>
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      • Retirement benefits including Provident Fund (PF) and Gratuity<\/span>
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      • ESI*<\/span>
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      • Complementary meal coupons<\/span>
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      • Company\-paid transportation<\/span>
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      • Sodexo benefits for income tax savings<\/span>
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      • Paternity & Maternity Leave Benefit<\/span>
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      • National Pension Saving<\/span>
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      • EL encashment<\/span>
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      • Sick Leave<\/span>

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