We are hiring passionate AI Solutions Engineers to work directly with our clients and deploy AI solutions that create measurable business outcomes.
As an AI Solutions Engineer, you will work shoulder-to-shoulder with client teams to understand their workflows, data, and operational challenges. Your primary goal will be to bridge the gap between business requirements and technology — implementing, customizing, and deploying AI-powered solutions within real-world production environments. This is a forward-deployed, client-embedded role where you own solutions from concept to production.
You will collaborate with clients, product teams, and internal engineers to integrate our AI platform into existing systems, ensuring reliable performance, seamless integrations, and measurable impact. This role is ideal for engineers who enjoy solving complex problems, working directly with customers, and delivering results quickly.
Location: Coimbatore, Tamil Nadu (Hybrid — on-site at client locations as required). Experience: 3–7 years.
Technologies: Full Stack (React.js / Node.js / Python / Mongo / Postgres SQL / AWS).
- Engage directly with clients to gather requirements, understand business workflows, and translate them into technical solutions.
- Design, build, and deploy AI-powered applications and integrations in client production environments.
- Develop responsive front-end interfaces using React.js / Angular and robust back-end services using Node.js / REST APIs.
- Integrate LLM APIs (OpenAI, Anthropic, etc.), AI/ML models, and third-party services into client systems.
- Customize and configure our AI platform to fit each client's infrastructure, data pipelines, and security requirements.
- Own end-to-end delivery — from proof-of-concept and sandbox testing through UAT and production go-live.
- Troubleshoot issues in live environments and provide rapid resolution with minimal client disruption.
- Document solution architecture, integration flows, and handover materials for client teams.
- Act as the technical face of the company — build trust with client stakeholders and identify opportunities for expanded engagement.
- B.E. / B.Tech / M.E. / M.Tech / MCA in Computer Science, IT, or related discipline.
- 3–7 years of hands-on full stack development experience.
- Strong proficiency in React.js and/or Angular, JavaScript/TypeScript, HTML5, CSS3.
- Solid back-end experience with Node.js, REST APIs, and microservices.
- Working knowledge of AI/LLM integration — prompt engineering, API-based model integration, RAG pipelines, or similar.
- Experience with cloud platforms (AWS preferred — Lambda, EC2, S3, API Gateway, Cognito).
- Familiarity with databases — PostgreSQL, MongoDB, or equivalent.
- Strong verbal and written communication skills in English — this is a client-facing role.
- Ability to work independently, manage ambiguity, and deliver under tight timelines.
- Experience with Python for AI/ML workflows.
- Exposure to CI/CD pipelines, GitHub Actions, Docker.
- Prior experience in a consulting, professional services, or client-embedded engineering role.
- Experience working with international clients across time zones.
- Opportunity to work on cutting-edge AI deployments with global clients.
- High-ownership, fast-paced environment with direct client exposure.
- Competitive compensation (CTC commensurate with experience).
- Immediate joiners / short notice period preferred.
- Design, build, and optimize LLM-powered agents for client-specific business use cases.
- Develop tool-calling workflows and agent orchestration systems to automate business processes.
- Engineer prompts, guardrails, and grounding mechanisms to ensure accurate and reliable responses.
- Implement retrieval and knowledge-grounding solutions that use approved data sources.
- Build evaluation frameworks and observability systems to measure agent quality, performance, and reliability.
- Analyze production data and continuously improve agent behavior through iteration and testing.
- Configure model routing strategies to balance capability, latency, and operational cost.
- Collaborate with clients to understand requirements and translate business objectives into AI solutions.
- Troubleshoot and improve AI systems running in production environments.
- Document AI workflows, evaluation methodologies, and deployment practices.
- Strong software engineering background with experience in modern programming languages.
- Hands-on experience building and deploying LLM-powered applications.
- Experience with prompt engineering, tool/function calling, retrieval systems, and agent workflows.
- Understanding of AI evaluation methodologies, testing strategies, and quality assurance processes.
- Experience implementing AI guardrails, safety mechanisms, and escalation workflows.
- Strong analytical and problem-solving skills.
- Ability to work with ambiguity and make sound engineering decisions.
- Excellent communication and collaboration skills.
- Strong attention to detail and a disciplined approach to validating AI-generated outputs.
- Experience with Amazon Bedrock and Claude on AWS.
- Experience with vector databases and retrieval-augmented generation (RAG) pipelines.
- Experience with speech-to-text (STT), text-to-speech (TTS), or voice AI applications.
- Experience with model fine-tuning and AI optimization techniques.
- AWS cloud infrastructure and Infrastructure as Code (IaC) experience.
- Prior consulting, solutions engineering, or customer-facing engineering experience.
