Fast Track Construction - AIOps Engineer

Job Title : AI Ops Engineer

Experience : 3+ Years

Location : PAN India

Employment Type : Full-Time

Job Summary :

We are seeking an innovative and technically proficient AI Ops Engineer with 3-5 years of experience in Python development, API integrations, and AI-driven solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, AI platforms, conversational AI, RAG architectures, and AI workflow automation. The role involves designing, deploying, optimizing, and operationalizing enterprise AI solutions while ensuring scalability, reliability, and cost efficiency.

Key Responsibilities :

- Design, develop, and implement AI-powered solutions using Large Language Models (LLMs).

- Create and optimize prompts for chatbots, virtual assistants, copilots, and enterprise AI applications.

- Build and deploy Retrieval-Augmented Generation (RAG) solutions to improve AI response accuracy and contextual relevance.

- Develop and integrate AI services with enterprise applications using REST APIs and integration frameworks.

- Implement AI-driven automation workflows to streamline business processes and improve operational efficiency.

- Configure and support conversational AI platforms and intelligent assistant solutions.

- Integrate AI models and services through API gateways and enterprise integration platforms.

- Monitor AI application performance, response quality, latency, and operational metrics.

- Optimize token consumption and manage token limits to improve cost efficiency and performance.

- Troubleshoot AI-generated outputs and continuously refine prompts and workflows to enhance accuracy.

- Support deployment, monitoring, and operationalization of AI services across development, testing, and production environments.

- Build reusable AI components, templates, and integration patterns for enterprise-wide adoption.

- Collaborate with architects, developers, product teams, and business stakeholders to identify AI use cases.

- Translate business requirements into scalable AI-enabled solutions.

- Conduct testing, validation, and performance evaluation of AI models and workflows.

- Implement security, governance, and compliance controls for AI applications.

- Create technical documentation, design specifications, and operational runbooks.

- Stay current with advancements in generative AI, LLMs, prompt engineering, and AI operations best practices.

- Support continuous improvement initiatives for AI platforms and automation frameworks.

- Participate in Agile development activities including sprint planning, reviews, and retrospectives.

Required Skillsets :

- Strong experience in Python development.

- Hands-on experience with API development and integrations.

- Good understanding of Large Language Models (LLMs) and Generative AI concepts.

- Experience with prompt engineering and prompt optimization techniques.

- Familiarity with AI platforms such as Claude, Gemini, GitHub Copilot, OpenAI, or similar technologies.

- Knowledge of Retrieval-Augmented Generation (RAG) architectures.

- Experience developing conversational AI and chatbot solutions.

- Strong understanding of REST APIs, API gateways, and enterprise integration patterns.

- Experience integrating AI services with enterprise applications.

- Knowledge of token management, token limits, and optimization strategies.

- Understanding of vector databases and semantic search concepts.

- Familiarity with AI orchestration frameworks and workflow automation tools.

- Knowledge of model evaluation, AI response testing, and performance monitoring.

- Experience with cloud platforms such as AWS, Azure, or Google Cloud.

- Understanding of AI security, governance, and responsible AI principles.

- Strong analytical thinking and problem-solving skills.

- Excellent communication, listening, and stakeholder management abilities.

- Ability to work effectively in cross-functional and Agile environments.

Preferred Qualifications :

- Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Engineering, or a related field.

- Experience with LangChain, LlamaIndex, Semantic Kernel, or similar AI frameworks.

- Exposure to vector databases such as Pinecone, Chroma, Weaviate, or FAISS.

- Experience with MLOps, AI Ops, or model deployment practices.

- Knowledge of CI/CD pipelines and DevOps methodologies.

- Familiarity with monitoring tools and observability platforms for AI applications.

- Experience building enterprise-scale AI assistants, copilots, or knowledge management solutions.

- Relevant certifications in AI, Cloud, Data Science, or Machine Learning technologies.