AI Developer

Wissen Technology is hiring forAI Developer

About Wissen Technology:

At Wissen Technology, we deliver niche, custom-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset—ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with 2000+ employees across offices in the US, UK, UAE, India, and Australia. Our commitment to excellence translates into delivering 2X impact compared to traditional service providers. How do we achieve this Through a combination of deep domain knowledge, cutting-edge technology expertise, and a relentless focus on quality. We don't just meet expectations—we exceed them by ensuring faster time-to-market, reduced rework, and greater alignment with client objectives. We have a proven track record of building mission-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome-based projects ensure predictable costs and timelines, while our agile pods provide clients with the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top-tier talent. Our mission is clear: to be the partner of choice for building world-class custom products that deliver exceptional impact—the first time, every time.

Job Summary:We are looking for an experienced AI/GenAI Engineer to design, develop, and deploy scalable AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI frameworks/workflow development. The ideal candidate should have strong Python development skills, hands-on experience with modern AI orchestration frameworks, and exposure to cloud-native AI deployments.

Experience:4- 10 Years

Location:Mumbai

Mode of Work:Hybrid

Key Responsibilities:

• Build and deploy GenAI applications using LLMs such as GPT, Gemini, Llama, Mistral, Claude, etc.
  
• Design and implement RAG pipelines using vector databases and embedding.
  
• Develop AI agents and workflow orchestration using LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
  
• Fine-tune, evaluate, and optimize LLM models for production use cases.
  
• Integrate AI services into scalable backend systems and APIs.
  
• Work with structured/unstructured datasets for NLP and AI workflows.
  
• Deploy AI solutions on cloud platforms such as Azure, AWS, or GCP.
  
• Build observability, monitoring, guardrails, and evaluation frameworks for GenAI systems.
  
• Collaborate with product, engineering, and business teams to deliver AI-driven solutions.
  
• Mentor junior engineers and contribute to AI architecture decisions (for senior roles)
  
  

Required Skills and Qualification

• 4–10 years of experience in AI/ML development or software engineering.
  
  
• Strong proficiency in Python for AI/ML development.
  
• Hands-on experience with LLMs and GenAI frameworks.
  
• Expertise in building RAG pipelines, embeddings, and vector search systems.
  
• Experience with LangChain, LlamaIndex, LangGraph, or similar orchestration frameworks.
  
• Knowledge of AI agents and workflow automation architectures.
  
• Experience integrating AI into APIs and microservices-based systems
  
• Familiarity with cloud platforms (AWS, Azure, GCP).
  
• Strong understanding of AI evaluation methods, model optimization, and guardrails.
  
• Solid problem-solving, analytical thinking, and communication skills.
  
  

Good to have Skills

• Experience building production-grade GenAI systems at scale.
  
• Exposure to multi-agent workflows and autonomous AI systems.
  
• Familiarity with AI observability tools and monitoring frameworks.
  
• Understanding of scalable backend architecture and distributed systems
  
• Experience working on enterprise AI products, copilots, or knowledge assistants.
  
• Exposure to fine-tuning, RLHF, or advanced model customization techniques.
  
  

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