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Salary
≈ $31k – $80k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Architect · 6+ years exp

Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 14, 2026.

Overview
Company
Impact
Profile match
HCLTech is a major Indian multinational information technology (IT) services and consulting company headquartered in Noida, Uttar Pradesh. Spun off from the original HCL Group in 1991, it ranks as one of India's largest technology companies alongside firms like TCS, Infosys, and Wipro.

Job Summary

Forward Deployed Engineer (FDE)

Role Overview

We are looking for a Forward Deployed Engineer to work directly with customers and engineering teams to identify high-value business problems and build, deploy, and productionize AI-powered solutions.

The FDE operates at the intersection of AI, software engineering, solution architecture, and customer problem-solving, taking solutions from initial discovery and rapid prototyping through production deployment and adoption.

Key Responsibilities

Key Responsibilities

· Work directly with customers and domain experts to understand business problems and identify high-impact AI use cases.

· Translate business requirements into practical AI/technical solutions.

· Rapidly prototype AI applications, agents, RAG systems, and workflow automations.

· Design and implement integrations with customer APIs, databases, enterprise systems, and existing applications.

· Build production-quality software using modern programming languages, APIs, cloud platforms, and AI/LLM technologies.

· Evaluate AI solutions for accuracy, reliability, latency, cost, and business impact.

· Troubleshoot real-world deployment challenges and iterate on solutions quickly.

· Collaborate with AI Architects, Product, Research, Security, and Engineering teams.

· Take ownership of deployments from discovery → prototype → production → handoff.

· Capture learnings from customer deployments and help turn them into reusable products, patterns, and platform capabilities.

Experience

· 6-10 years of professional software engineering experience, with strong backend, full-stack, platform engineering, or solution delivery experience.

· 2+ years of hands-on experience building AI/GenAI solutions using LLMs, RAG, AI Agents, or enterprise AI platforms.

· Experience designing, deploying, and supporting production applications in enterprise environments.

· Experience working directly with customers, business users, or stakeholder-facing project teams

Skill Requirements

Required Skills

Technical

· Strong software engineering and programming fundamentals.

· Experience building production applications and integrating APIs.

· Good understanding of LLMs, prompt engineering, RAG, embeddings, vector databases, and AI agents.

· Familiarity with cloud platforms, databases, authentication, security, and enterprise integrations.

· Ability to debug and solve complex technical problems independently.

· Understanding of AI evaluation, observability, guardrails, and production reliability.

· Hands-on experience with Azure, AWS, or GCP cloud platforms.

· Experience with Docker, Kubernetes, CI/CD, and cloud-native deployment practices.

· Knowledge of LLMOps including monitoring, evaluation, tracing, prompt/model versioning, latency optimization, and cost management.

· Experience with SQL/NoSQL databases, ETL pipelines, message queues, streaming systems, and enterprise data integration.

· Familiarity with authentication, security, governance, and enterprise integration patterns.

· Ability to debug and solve complex technical problems independently.

· Understanding of AI evaluation, observability, guardrails, and production reliability.

Problem Solving

· Ability to work with ambiguous requirements.

· Strong analytical and troubleshooting skills.

· Ability to quickly prototype and validate ideas.

· Customer and business-oriented thinking.

Collaboration

· Excellent communication and stakeholder-management skills.

· Comfortable working directly with customers and senior business/technical stakeholders.

· Ability to explain complex AI concepts in simple business terms.

· Ability to collaborate across Architecture, Engineering, Product, Research, Security, and Sales/GTM teams.

Other Requirements

Good Communication Skills

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