Job Description :-
| Company: | Guidehouse |
| Job Role: | AI Software Engineer |
| Batches: | 2021-2025 |
| Degree: | Bachelor’s degree |
| Experience: | 1–5 years |
| Location: | Chennai Trivandrum, India |
| CTC/Salary: | INR 6-21 LPA (Expected) |
What You Will Do
- 1–5 years of experience in software engineering and production-quality Agentic AI Systems.
- Experience of generating code using prompts and navigating fluidly through generated code using GitHub Copilot or OpenAI Codex or similar platforms
- Design, build, evaluate, deploy, and maintain AI-enabled and agentic applications for enterprise use cases.
- Develop backend services and orchestration layers using Python and frameworks such as FastAPI, Flask, or Django; TypeScript/Node.js experience is also valuable.
- Collaborate with front-end teams using React, Next.js, Angular, or Vue.js to deliver high-quality user experiences.
- Build AI application workflows that use LLMs, retrieval and grounding, tools, structured outputs, and APIs to complete business tasks reliably.
- Build and integrate REST and/or WebSocket APIs and connect applications to internal and external tools, services, and enterprise data sources.
- Deploy and operate applications on at least one cloud platform such as Azure, AWS, or GCP/Vertex AI.
- Create and maintain evaluations for AI features and agent workflows, including quality checks, regression testing, and task-success criteria.
- Participate in code reviews, testing, documentation, and continuous improvement of engineering workflows.
What You Will Need
- Strong software engineering fundamentals and hands-on experience building production-grade applications, services, APIs, or microservices.
- Proficiency in one or more backend languages such as Python, Java, or TypeScript/Node.js.
- Experience with modern front-end frameworks such as React, Angular, Vue.js, or Next.js, or strong collaboration experience with UI engineers.
- Experience designing and consuming REST and/or WebSocket APIs and integrating with databases, services, and external systems.
- Hands-on experience with at least one major cloud platform such as Azure, AWS, or GCP/Vertex AI.
- Interest in or hands-on experience building production AI systems, including LLM-powered features, agentic workflows, or intelligent automation use cases.
- Experience applying software engineering discipline to AI systems, including testing, evaluation, iteration, and production readiness.
- Experience using Git and standard engineering practices such as branching, code reviews, issue tracking, and CI/CD.
- Experience working in Agile teams and managing delivery through tools such as Jira.
- Ability to learn quickly and apply strong engineering judgment while working across evolving AI technologies and application requirements.
What Would Be Nice to Have
- Experience building AI applications with LLM integrations, retrieval or grounding systems, vector search, tool or function calling, or agent frameworks.
- Experience evaluating AI applications and agent workflows using test datasets, automated checks, grader-based evaluations, and regression testing.
- Experience with observability and tracing for distributed or AI systems, including logs, metrics, traces, and production debugging.
- Experience with security controls for AI applications, including access control, secrets handling, guardrails, prompt-injection awareness, and human-in-the-loop approvals where appropriate.
- Experience with CI/CD, automated deployments, GitHub Actions, or similar engineering delivery pipelines.
- Experience in rapid prototyping and iterative product development.
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Experience building low-code solutions using Power Apps, Copilot Studio, or similar platforms.