Associate

Key Responsibilities

• Design, build, and maintain AI-powered applications using LLMs (especially OpenAI Models) and related technologies.
• Implement Python-based API integrations with LLM platforms for use cases such as summarization, classification, extraction, reasoning, and workflow automation.
• Develop prompt engineering strategies and reusable prompt frameworks for AI outputs.
• Build AI agents and tools that orchestrate multi-step workflows, tool calling, and interaction with data sources.
• Collaborate with consultants and case teams to translate business problems into AI solutions.
• Evaluate and experiment with emerging AI frameworks, libraries, and tools.
• Support supervisors in work planning, solution design, and brainstorming for AI initiatives.
• Ensure solutions are robust, secure, well-documented, and aligned with engineering and governance standards.
• Communicate technical concepts and insights clearly to non-technical stakeholders.
• Proactively drive self-learning in AI, LLMs, and applied machine learning.
• Contribute to knowledge sharing, documentation, and internal training.

Requirements & Tech Stack

• Strong programming skills in Python and/or JavaScript/TypeScript.
• Hands-on experience with LLM APIs such as OpenAI and Anthropic, including prompt design and response handling.
• Experience building AI agents, workflows, or automation tools using LLMs.
• Ability to build evaluation sets, guardrails, and regression checks for LLM outputs.
• Understanding of context engineering techniques and LLM limitations.
• Familiarity with REST APIs and integrating external services.
• Working knowledge of data structures, basic algorithms, and software engineering best practices.
• Experience using version control systems such as Git.
• Ability to work in a fast-paced environment with evolving requirements.
• Strong problem-solving and analytical thinking skills.
• Excellent English communication skills.

Good-to-have skills

• Experience with AI orchestration frameworks (e.g., LangChain, LlamaIndex).
• Exposure to vector databases and embeddings (e.g., FAISS, Pinecone, Chroma).
• Basic understanding of machine learning concepts and NLP.
• Familiarity with modern front-end technologies such as Angular, React, and HTMX.
• Familiarity with cloud platforms (AWS, Azure, or GCP).
• Experience building internal tools, prototypes, or dashboards.
• Ability to write clear technical documentation and usage guides.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Strong academic credentials, analytical ability, and problem-solving skills.
• For Undergraduate degree: 2 - 4 years of experience in software development, AI engineering, or related roles.
• For Postgraduate degree: 0 - 2 years of relevant experience.
• Prior exposure to consulting, analytics, or business problem-solving environments is preferred but not mandatory.