AI Solutions Engineer

Job Title - AI Solutions Engineer

Key Skills - AI-Driven Solutions, Agentic Workflows, AI Agents.

Experience - 3-5 Years

Location - Remote

Shift - General

We at Coforge are seeking an AI Solutions Engineer with the following skill set.

Role Overview

Coforge is looking for an AI Solutions Engineer to design, deploy, and scale AI-driven solutions directly within customer environments. This role focuses on delivering intelligent, agent-based systems on Coforge’s AI Cloud, working closely with customers to rapidly move from concept to production—often within weeks. This is a hands-on, delivery-oriented opportunity at the intersection of applied AI, cloud engineering, and customer engagement.

Key Responsibilities

• Design, build, and deploy AI agents and agentic workflows in live customer environments.

• Integrate AI systems with enterprise workflows, APIs, data pipelines, and operational platforms.

• Develop reasoning-based, planning-driven, tool-enabled, and multi-agent AI systems.

• Implement orchestration and automation using platforms such as n8n, Temporal, Prefect, or Dagster.

• Apply MCP (Model Context Protocol), function calling, guardrails, retries, and human-in-the-loop controls.

• Write production-grade code in Python and/or TypeScript.

• Ensure reliability, security, observability, and performance of deployed AI solutions.

• Collaborate closely with customer engineering, data, and operations teams.

• Generalize customer implementations into reusable agent frameworks, patterns, and best practices.

Required Skills & Experience

• At least 3-5 years of experience designing and delivering software systems, applied AI solutions, or AI-enabled platforms in real-world settings.

• Proven hands-on experience developing AI agents or agent-based workflows through professional work, research, or open-source contributions.

• Practical exposure to modern agent frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, LlamaIndex Agents, Haystack, or comparable technologies.

• Experience building automated or orchestrated workflows using tools like n8n, Temporal, Prefect, Dagster, or similar platforms.

• Strong working knowledge of large language models (LLMs), prompt design, planning and execution strategies, tool-enabled agents, and MCP / function-calling architectures.

• Strong programming capability in Python and/or TypeScript for building production-ready systems.

• Demonstrated ability to quickly onboard onto new platforms and deliver functional solutions under tight timelines.

• Comfort collaborating directly with customers and stakeholders in fast-paced, ambiguous environments.

• Excellent communication skills with a strong sense of ownership and problem-solving mindset.

Bonus Experience That Will Set You Apart

• Experience taking AI-powered systems from development into production, particularly in regulated or compliance-sensitive environments.

• Familiarity with healthcare datasets, clinical or operational workflows, or enterprise-scale data platforms.

• Hands-on experience designing or operating cloud-native solutions on AWS, Azure, or Google Cloud.

• Exposure to monitoring, evaluation, tracing, or observability practices for AI-driven or agent-based systems.

• Background in customer-facing engineering roles such as solutions engineering, consulting, or forward-deployed technical delivery.