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Hiring for a Client - Eureka Digitisation & Automation Services
Roles & Responsibilities
This is a foundational role blending applied machine learning, LLM integration, and modern data
engineering to drive real-time decisioning and automation across the platform.
Key Responsibilities
•Lead implementation of LLM-based features: summarization, sentiment detection, auto-disposition,
escalation tagging
•Fine-tune and evaluate models (Whisper, GPT, HuggingFace, Rasa) for vernacular (Indian) language
support
•Build and deploy LangChain pipelines for prompt engineering, QA tagging, and agent assist
•Prototype emotion recognition, contextual agent replies, and real-time assist layer
•Build and maintain inference pipelines using FastAPI, Docker, Kubernetes
•Integrate AI modules into core product features (Dialer, CRM sync, IVR)
•Optimize model latency and deployment strategy for high concurrency environments
•Architect scalable data pipelines using PostgreSQL, Redis, and Kafka
•Build ETL/ELT workflows to support real-time analytics, dashboards, and feedback loops
•Maintain secure, compliant data storage, retrieval, and access control pipelines (DPDP, GDPR-ready)
Collaboration & Leadership
•Work closely with Product, Engineering, and UX to deliver features that directly impact agent
productivity
•Guide junior ML and data engineers; define and enforce coding/data standards
•Contribute to AI strategy, model governance, and data infrastructure roadmap
Ideal Candidate
1Strong Principal AI Engineer (Agentic AI / Voice Bot / LLM Engineering) Profiles
2Mandatory (Experience 1) – Must have 6+ years of overall software engineering experience, with at least 3+ years of hands-on experience in Artificial Intelligence, Machine Learning, Generative AI, or Applied AI engineering roles.
3Mandatory (Experience 2) – Must have strong hands-on experience designing, developing, and deploying AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and Generative AI architectures.
4Mandatory (Experience 3) – Must have minimum 1+ year of recent hands-on experience in Voice Bot Development, Voice AI, Conversational AI, AI Voice Agents, Speech AI, Contact Center Automation, or Voice Automation Platforms.
5Mandatory (Experience 4) – Must have strong expertise in Python and should have built scalable AI/ML applications, APIs, microservices, or backend systems using Python-based frameworks.
6Mandatory (Experience 5) – Must have hands-on experience with AI/LLM frameworks such as LangChain, LangGraph, Hugging Face, LlamaIndex, CrewAI, AutoGen, Whisper, OpenAI SDKs, or equivalent GenAI development frameworks.
7Mandatory (Notice Period) – Immediate Joiners or candidates who can join within 15 days will be highly preferred.
8Preferred (Cloud) – Experience with AWS, Azure, GCP, MLOps, AI deployment platforms, model serving infrastructure, and cloud-native architectures.
Job ID: 153413321
Skills:
Microservices, Java, Testing, Kubernetes, Docker, Git, async programming, RAG pipelines, Crew.ai, cloud-native architecture, knowledge retrieval systems, embedding models, vector databases, RAG systems, LLM optimization techniques, LangChain, Autogen, prompt engineering, advanced Python programming
Skills:
Git, Docker, Kubernetes, Python, LangChain, LLM optimization techniques, RAG systems, vector databases, embedding models, prompt engineering
Skills:
Kubernetes, Microservices, Java, Typescript, cloud, Python, Apis, MCP tools, data integrations, authentication patterns, event-driven systems, CI CD, observability, RAG, workflow orchestration
Skills:
Ml, Uipath, Node.js, Angular, React, REST, Gcp, Docker, Flask, FastAPI, Kubernetes, Python, Ai, GRPC, Llm, WebSockets, Agentic AI, RAG, Streamlit, Langraph
Skills:
Java, Apis, Microservices, cloud, Typescript, Python, Kubernetes, GenAI, agentic AI, workflow orchestration, agent patterns, CI CD, Llm, Evaluation, RAG, MCP tool calling context engineering, business-process decomposition, observability