Responsibilities
- Design, implement, and maintain end-to-end AI applications, including chatbots, Q&A platforms, and agent workflows
- Collaborate directly with clients to understand their needs, identify opportunities, and recommend LLM-driven solutions
- Develop and manage robust data pipelines, prompt strategies, and datasets to ensure effective and accurate AI models (Will be a plus)
- Evaluate and refine AI system performance, ensuring outputs are accurate, secure, scalable, and compliant with industry regulations (Will be a plus)
- Conduct research and rapid prototyping to validate technical feasibility and demonstrate business value of AI solutions
- Stay current with evolving LLM technologies, frameworks, and methodologies to continuously improve solutions and client outcomes
Basic qualifications
- Strong proficiency in Python, experience with web frameworks like FastAPI or similar
- Understanding of the AI application development lifecycle
- Experience with rapid UI prototyping using Streamlit, Gradio, or similar frameworks
- Familiarity with major LLM platforms and APIs (OpenAI, Anthropic, Amazon Bedrock, Gemini) and related frameworks (LangGraph, LlamaIndex, Strands Agents, etc.)
- Knowledge of advanced AI integration patterns (e.g., RAG, Agents)
- Experience deploying AI solutions at scale, with considerations for performance, cost-efficiency, and maintainability
- Proven ability to evaluate generative AI quality using metrics such as retrieval and classification scores, as well as LLM-based evaluation methods
- Proven experience in AI engineering and delivering ML-based solutions
- Strong problem-solving skills and attention to detail
- Excellent communication, collaboration, and interpersonal skills
Preferred qualifications
- Experience designing experiments, conducting A/B tests, and iterating on models based on user feedback
- Understanding of retrieval systems (keyword search, vector search, embeddings) and ranking algorithms
- Familiarity with emerging protocols such as MCP, A2A, ACP, etc.
- Experience deploying to cloud AI platforms (Azure OpenAI, Amazon Bedrock, GCP Vertex AI) or on-premise solutions (e.g., vLLM)
- Experience with enterprise AI platforms such as AWS AgentCore or Databricks AgentBricks or Google Agents Space, or Azure AI Foundry
- Experience with observability and monitoring tools and frameworks
- Python, PyTorch, Hugging Face, LangChain
- Vector databases including Qdrant, FAISS, Chroma
- APIs for LLMs such as Azure OpenAI and AWS Bedrock
- CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT Diversity of assignments and projects Personal development plan Mentoring programs and leadership development Certification and professional development support Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses English courses taught by certified teachers
- Diversity of assignments and projects
- Personal development plan
- Mentoring programs and leadership development
- Certification and professional development support
- Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses
- English courses taught by certified teachers
- CORPORATE BENEFITS Extra leave days Referral bonuses
- Extra leave days
- Referral bonuses
- COMPENSATION PACKAGE Competitive compensation paid in USD Regular salary and performance reviews
- Competitive compensation paid in USD
- Regular salary and performance reviews
- MEDICAL & HEALTHCARE Private health insurance
- Private health insurance
- WORKING ENVIRONMENT Recreation office zones with tea, coffee and snacks Sports and game consoles IT equipment and Microsoft's Software Assurance Home Use Program (HUP)
- Recreation office zones with tea, coffee and snacks
- Sports and game consoles
- IT equipment and Microsoft's Software Assurance Home Use Program (HUP)
Tags & focus areas
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