Posted 31 May, 2026
559660 | IC | AI Engineer | Bengaluru
ClifyX
Bengaluru,Karnataka,India
Full Time
Reference: 365_594563_26-02847
About the Role
We are seeking a visionary AI Engineer to spearhead our AI and advanced analytics initiatives within the Customer & Agency domain. While this role contributes to strategic impact, it is first and foremost a hands on engineering position. This opportunity is ideal for a seasoned professional who thrives at the intersection of cutting edge technology, ethical AI, and real-world implementation. You will personally design, build, test, deploy, and optimize high-impact AI systems—ranging from Generative AI, Agentic AI, LLM-driven conversational solutions, and intelligent document Processing that transforms customer servicing and agency workflows.
Key Responsibilities
• Conversational AI Ownership: Lead the architecture, development and optimization of, Intelligent Document Processing, intelligent chatbots and conversational agents, including RAG pipelines, tool/function calling, memory, and multi agent workflows (e.g., LangChain/LangGraph/Hugging Face).
• Application & Platform Engineering: Build production grade microservices/APIs (FastAPI/Flask); integrate with enterprise systems (CRM, claims, knowledge bases) and manage channel integrations (web, mobile, contact center).
• Cloud Native Deployments: Deploy to Azure , GCP (Container Apps/Functions/Cloud Run); manage secrets (Key Vault/KMS), configuration, autoscaling, and reliability.
• CI/CD & Release Practices: Establish automated tests, canary/blue green deployments, rollback strategies, and artifact versioning (models/prompts/flows) with MLflow/Azure ML.
• Model Development & Deployment: Build, test, deliver, and maintain robust AI systems and services that solve complex business challenges—spanning LLM applications, retrieval, and inference APIs.
• Business Alignment: Influence and translate strategic business objectives into actionable technical requirements, system design, and success metrics.
• Health Pillar Support: Drive ideation and delivery of AI solutions within the health vertical—especially AI based conversational chatbots and agentic assistants.
• Responsible AI Leadership: Embed the highest standards of AI ethics and Responsible AI in all phases of solution design, deployment, and operations.
• Collaboration & Cross Functional Delivery: Partner closely with Data Science, Engineering, Product, UX, Risk/Compliance, and Operations to plan, ship, and iterate LLM systems; coordinate with channel teams; co create runbooks and ensure smooth handoffs to operations.
• Innovation & Thought Leadership: Continuously explore and implement best in class solutions in Generative and Agentic AI, platform components, and reusable accelerators.
• Security & Responsible AI Guardrails: Enforce PII redaction, content moderation, red teaming, policy compliance, and audits aligned to enterprise governance and APAC regulations.
• Performance & UX: Tune for low latency, high reliability, and high quality conversational UX, including handoffs, feedback loops, and continuous evaluations.
Qualifications & Skills
Qualification Details
Education Bachelor's or master's in data science, Computer Science, AI, or related quantitative field
Experience 5+ years (Bachelors) or 3+ years post-Masters in AI/Data Science
Programming (must)Expert in Python, SQL, LangChain, LangGraph, Hugging Face(similar)
Good to have FastAPI/Flask, Docker, and Git-based CI/CD
Use-Case Experience Preferably with conversational chatbots utilizing LLMs for intent detection, AI based routing, LLM based OCR and Intelligent Document Processing (mandatory to have hands-on on at least one)
Cloud Platforms Hands-on experience with Azure or Google Cloud
MLOps/LLMOps Experience in prompt/version registries, observability, canary releases, and rollback. Prior experience in managing ML artifacts, LLM cost optimization is a strong plus
Security & RAI Guardrails Experience implementing PII protection, content filters, safety policies, red teaming, and compliance audits
Observability & Cost Controls Hands-on with telemetry, SLOs, alerting, and token/latency optimization strategies
Leadership Experience in leading delivery teams of AI engineers, LLM application standards and reusable components is a plus
Communication Exceptional ability to communicate across technical and non-technical audiences
Collaboration Strong team player with cross-functional and cross-geography collaboration skills
Problem Solving Demonstrated critical thinking and analytical capabilities
We are seeking a visionary AI Engineer to spearhead our AI and advanced analytics initiatives within the Customer & Agency domain. While this role contributes to strategic impact, it is first and foremost a hands on engineering position. This opportunity is ideal for a seasoned professional who thrives at the intersection of cutting edge technology, ethical AI, and real-world implementation. You will personally design, build, test, deploy, and optimize high-impact AI systems—ranging from Generative AI, Agentic AI, LLM-driven conversational solutions, and intelligent document Processing that transforms customer servicing and agency workflows.
Key Responsibilities
• Conversational AI Ownership: Lead the architecture, development and optimization of, Intelligent Document Processing, intelligent chatbots and conversational agents, including RAG pipelines, tool/function calling, memory, and multi agent workflows (e.g., LangChain/LangGraph/Hugging Face).
• Application & Platform Engineering: Build production grade microservices/APIs (FastAPI/Flask); integrate with enterprise systems (CRM, claims, knowledge bases) and manage channel integrations (web, mobile, contact center).
• Cloud Native Deployments: Deploy to Azure , GCP (Container Apps/Functions/Cloud Run); manage secrets (Key Vault/KMS), configuration, autoscaling, and reliability.
• CI/CD & Release Practices: Establish automated tests, canary/blue green deployments, rollback strategies, and artifact versioning (models/prompts/flows) with MLflow/Azure ML.
• Model Development & Deployment: Build, test, deliver, and maintain robust AI systems and services that solve complex business challenges—spanning LLM applications, retrieval, and inference APIs.
• Business Alignment: Influence and translate strategic business objectives into actionable technical requirements, system design, and success metrics.
• Health Pillar Support: Drive ideation and delivery of AI solutions within the health vertical—especially AI based conversational chatbots and agentic assistants.
• Responsible AI Leadership: Embed the highest standards of AI ethics and Responsible AI in all phases of solution design, deployment, and operations.
• Collaboration & Cross Functional Delivery: Partner closely with Data Science, Engineering, Product, UX, Risk/Compliance, and Operations to plan, ship, and iterate LLM systems; coordinate with channel teams; co create runbooks and ensure smooth handoffs to operations.
• Innovation & Thought Leadership: Continuously explore and implement best in class solutions in Generative and Agentic AI, platform components, and reusable accelerators.
• Security & Responsible AI Guardrails: Enforce PII redaction, content moderation, red teaming, policy compliance, and audits aligned to enterprise governance and APAC regulations.
• Performance & UX: Tune for low latency, high reliability, and high quality conversational UX, including handoffs, feedback loops, and continuous evaluations.
Qualifications & Skills
Qualification Details
Education Bachelor's or master's in data science, Computer Science, AI, or related quantitative field
Experience 5+ years (Bachelors) or 3+ years post-Masters in AI/Data Science
Programming (must)Expert in Python, SQL, LangChain, LangGraph, Hugging Face(similar)
Good to have FastAPI/Flask, Docker, and Git-based CI/CD
Use-Case Experience Preferably with conversational chatbots utilizing LLMs for intent detection, AI based routing, LLM based OCR and Intelligent Document Processing (mandatory to have hands-on on at least one)
Cloud Platforms Hands-on experience with Azure or Google Cloud
MLOps/LLMOps Experience in prompt/version registries, observability, canary releases, and rollback. Prior experience in managing ML artifacts, LLM cost optimization is a strong plus
Security & RAI Guardrails Experience implementing PII protection, content filters, safety policies, red teaming, and compliance audits
Observability & Cost Controls Hands-on with telemetry, SLOs, alerting, and token/latency optimization strategies
Leadership Experience in leading delivery teams of AI engineers, LLM application standards and reusable components is a plus
Communication Exceptional ability to communicate across technical and non-technical audiences
Collaboration Strong team player with cross-functional and cross-geography collaboration skills
Problem Solving Demonstrated critical thinking and analytical capabilities
