Consultant_AI Observability

HCLSoftware; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

HCLSoftware is seeking an expert in the Professional Services Team to help build and deploy AI Observability solutions. This role sits at the intersection of product engineering, professional services, and pre-sales support, collaborating with engineering to shape product features and engaging with customers through workshops, requirement discussions, solution deployment, and UAT.

You will configure and deploy AI Observability products, act as a trusted technical advisor, document architectures,

Qualifications

• BE / B.Tech / ME / M.Tech in Computer Science or Data Science; AI/ML major preferred.
• Hands-on with AI/LLM Observability tools like MLflow, Arize, Langfuse or DeepEval.
• Strong understanding of Observability concepts (logging, metrics, tracing) and RAG.

Responsibilities

• Lead discovery workshops to gather AI Observability requirements.
• Configure and deploy AI Observability solutions in customer environments.
• Provide technical guidance during implementation and operations; document guides.

Skills

Python development

AI/LLM Observability

Multi-Agent workflows

Workshop leadership

Customer-facing

Education

BE/B.Tech / ME / M.Tech in CS/Data Science

Tools

MLflow

Arize AI

Langfuse

DeepEval

Job description

We are looking for an expert in Professional Services Team to help build and deploy AI Observability solutions.

This role sits at the intersection of product engineering, professional services, and pre-sales support. The

candidate will work closely with the engineering and development teams to shape AI Observability product

features, and will also engage directly with customers through workshops, requirement discussions, solution

deployment, and UAT to ensure these capabilities solve real-world problems for running AI/ML and GenAI

applications in production.

Job Duties

Professional Services

• Lead and participate in discovery workshops with customers to understand their AI Observability
• requirements (monitoring, tracing, evaluation, cost/latency tracking, model/agent performance, RAG
• Create solution designs and deployment plans.
• Configure, customize, and deploy AI Observability products/solutions within customer environments.
• Act as a trusted technical advisor to customers throughout implementation and then in operations as well,
• ensuring successful adoption. Should be available to provide escalated support in operations.
• Document solution architecture, configurations, and deployment guides for customer and internal use.

Product & Engineering Collaboration

• Work closely with the engineering/development team on the design and development of AI Observability
• related product features.
• Research industry trends, emerging tools, and competitive products in the AI Observability / LLM
• Observability space to support product roadmap planning.
• Translate customer and market insights into clear, actionable Product Requirement Documents (PRDs).
• Perform User Acceptance Testing (UAT) as part of product release cycle and provide structured feedback to
• the development team to improve product quality and fit.

Cross-Functional Coordination

• Serve as the link between customer-facing needs and the engineering roadmap, ensuring the voice of the
• customer is represented in product decisions.
• Collaborate with sales/pre-sales teams on scoping, technical qualification, and solution demonstrations as
• needed.

Skills

• Education Requirement: BE / B.Tech / ME / M.Tech in Computer Science or Data Science. AI/ML major /
• stream is preferred.
• Must have hands-on experience with one or more AI/LLM Observability or evaluation tools such as
• MLflow, Arize (Arize AI / Phoenix), Langfuse, DeepEval or similar platforms used to monitor, trace and
• evaluate AI/ML and GenAI applications.
• Good understanding of traditional Observability / APM concepts (logging, metrics, tracing, alerting) and
• how they map to AI-specific observability needs.
• Strong conceptual understanding of RAG (Retrieval-Augmented Generation) architectures, AI/ML
• models (traditional ML and deep learning fundamentals), and GenAI / Agentic AI concepts and design
• patterns.
• Familiarity with agentic/orchestration frameworks such as CrewAI, LangGraph, LangChain or similar.
• Must have strong Python development skills and experience in developing AI/ML based applications.
• Experience in development of Multi-Agent application for complex workflows is preferred.
• Ability to write clear technical documentation, including Product Requirement Documents (PRDs) and
• deployment/solution guides.
• Strong communication and stakeholder-management skills; comfortable leading workshops and discussions
• directly with customers.
• Employs positive thinking and is able to work constructively in team development.

Good to Have

• Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, Chroma).
• Experience with LLM providers/APIs (OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, etc.).
• Familiarity with containerization and deployment tooling (Docker, Kubernetes) for on-prem / customer-
• Exposure to CI/CD pipelines and public cloud platforms (AWS / Azure / GCP).
• Prior experience in a Professional Services, Solutions Engineering, or Technical Consulting role