Forward Deployed Software Engineer

Cascades Data Solutions India; India; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

Telesat is seeking a Forward Deployed AI Engineer to turn AI prototypes into production-ready solutions within real engineering environments. You will collaborate with system test, automation, QA, and software teams to deliver reliable AI-driven improvements and workflows.

The role focuses on deploying AI-powered automation, integrating with enterprise apps, and building scalable orchestration using Python. Strong debugging and collaboration skills are essential.

Qualifications

• 2+ years of hands-on software engineering, AI, or related field.

Responsibilities

• Turn LLM prototypes into production-ready, repeatable solutions.

Skills

Python development

AI deployment

REST APIs

Git

CI/CD

Problem solving

Team collaboration

Tools

Docker

Kubernetes

AWS

Azure

GCP

Linux

Job description

Forward Deployed AI Engineer – LLM & AI Automation

Telesat is looking for a Forward Deployed AI Engineer (FDE) to help bring AI from prototypes into real-world engineering environments.

In this role, you’ll work closely with system test engineers, automation teams, QA, and software development teams to identify opportunities for AI, build practical solutions, and make them reliable enough for production use.

This is a hands-on engineering role for someone who enjoys solving ambiguous problems, working closely with users, and turning AI capabilities into measurable improvements in engineering productivity.

What You'll Do

AI Deployment & Automation

• Take LLM and Generative AI prototypes and turn them into production-ready, repeatable solutions.
• Integrate AI solutions with existing engineering applications, automation frameworks, APIs, and workflows.
• Build orchestration and integration logic across multiple systems using Python.
• Deploy, monitor, troubleshoot, and continuously improve AI-powered solutions.

AI in System Test Automation

You'll work directly with system test and automation teams to:

• Understand real-world testing workflows, constraints, and failure modes.
• Identify areas where AI can safely reduce manual effort and improve productivity.
• Adapt AI workflows to work with existing automation frameworks, test data, schemas, and configurations.
• Develop AI-powered workflows that assist with generating structured test assets.
• Use real test results and failure analysis to continuously improve AI behavior.

Agentic AI

• Implement and customize agentic AI workflows for engineering and test automation use cases.
• Develop AI workflows that can interpret requirements, schemas, and models.
• Tune prompts, instructions, and AI behavior based on real-world outcomes.
• Build validation and guardrails to improve the accuracy, reliability, and safety of AI outputs.
• Diagnose and resolve AI-related issues in live engineering environments.

Collaboration & Problem Solving

• Work closely with engineers and end users to understand their challenges and workflows.
• Rapidly iterate on solutions based on real-world feedback.
• Debug complex software and AI issues across multiple systems.
• Help engineering teams identify practical and high-value opportunities for AI adoption.

Required Qualifications

• 2+ years of hands-on experience in software engineering, applied AI, or a related field.
• Strong hands-on Python development experience.
• Experience deploying LLM / Generative AI applications beyond the prototype stage and into real-world or production environments.
• Experience integrating AI solutions with enterprise applications, automation frameworks, APIs, or other software systems.
• Demonstrated experience taking an AI or automation solution from prototype to real-world usage.
• Experience troubleshooting and improving AI behavior, including:
• Prompt/instruction tuning
• Output validation
• Guardrails
• Failure analysis
• Diagnosing inaccurate or low-quality outputs
• Strong software engineering, debugging, and problem-solving skills.
• Experience working closely with engineers or end users and iterating solutions based on live feedback.
• Experience with REST APIs, Git, CI/CD, and at least one major cloud platform such as AWS, Azure, or GCP.

Nice to have experience with:

• Networking: TCP/IP, MPLS, gNMI, YANG
• Linux
• Docker
• Kubernetes
• Test automation frameworks
• System or network testing environments.

You'll help Telesat's engineering teams:

• Reduce manual testing and engineering effort.
• Automate complex workflows.
• Improve the speed and quality of system testing.
• Turn promising AI prototypes into dependable production solutions.
• Establish practical and responsible ways of using Agentic AI in engineering environments.