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Salary
≈ $12k – $36k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 6+ years exp

Confirmed on the employer's own hiring board on Oct 15, 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

Role Overview :

We are looking for a Forward Deployment Engineer (AI/ML/Python) to join our Customer Implementations team. You will design and build Python-based integrations, data pipelines, APIs, and AI-enabled workflows while partnering closely with customers and internal teams to ensure successful deployments. This is a highly visible, customer-facing role that combines hands-on coding, technical problem-solving, and solution delivery.

Key Responsibilities

What You'll Do

Python Development & Integrations

  • Design, develop, and maintain Python-based services, APIs, and integration frameworks.
  • Build scalable data ingestion, transformation, and validation pipelines.
  • Develop customer-specific integrations, automations, and business workflows.
  • Create reusable implementation accelerators and integration components.

AI & Intelligent Workflow Implementations

  • Integrate LLM, NLP, RAG, and AI-powered capabilities into enterprise environments.
  • Work alongside ML Engineers to deploy and optimize AI models in production.
  • Support embedding pipelines, retrieval systems, and intelligent resolution workflows.
  • Enable customers to leverage AI capabilities effectively within their existing ecosystems.

Deployment & Reliability

  • Deploy and manage solutions across Azure, AWS, and GCP environments.
  • Ensure reliability, scalability, observability, and performance of deployed services.
  • Troubleshoot production issues, analyze logs, and perform root-cause analysis.
  • Implement monitoring and operational best practices.

Customer Delivery & Solution Ownership

  • Partner with Customer Success, Product, and Engineering teams to understand customer requirements.
  • Translate business needs into scalable technical solutions.
  • Own end-to-end implementation and deployment for strategic enterprise customers.
  • Provide technical guidance, architecture recommendations, and implementation best practices.

Technical Leadership

  • Participate in architecture discussions and code reviews.
  • Mentor junior engineers and share implementation best practices.
  • Drive technical excellence through automation, documentation, and reusable frameworks.
  • Codify successful implementation patterns into tools, playbooks, and accelerators.

Skill Requirements

Required Qualifications

  • 6+ years of professional software engineering experience.
  • 5+ years of hands-on Python development experience.
  • Experience implementing AI-powered solutions, integrations, or customer-facing technical projects.
  • Strong understanding of backend systems, microservices, and distributed architectures.
  • Experience building REST APIs using FastAPI, Flask, or Django.
  • Hands-on experience with relational and NoSQL databases such as PostgreSQL and MongoDB.
  • Experience working with cloud platforms including Azure, AWS, or GCP.
  • Strong debugging, troubleshooting, and problem-solving skills.
  • Excellent communication and stakeholder management skills.
  • Proven experience working directly with customers and managing technical implementations.

Delivery & Execution Mindset

  • Ability to scope work, sequence delivery, and proactively remove blockers.
  • Strong decision-making skills with the ability to balance scope, quality, and timelines.
  • Willingness to contribute directly to code and technical problem-solving when needed.
  • Ability to drive clarity and execution across cross-functional teams.

Other Requirements

Preferred Qualifications

  • Experience with LLMs, RAG architectures, NLP, or AI-powered applications.
  • Knowledge of Java and enterprise integration patterns.
  • Experience with Agentic AI frameworks and intelligent workflow automation.
  • Hands-on experience with Docker, Kubernetes, and containerized deployments.
  • Familiarity with Kafka, RabbitMQ, or event-driven architectures.
  • Experience with CI/CD pipelines and DevOps practices.
  • Startup or high-growth SaaS experience.
  • Open-source contributions or technical thought leadership.
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