Machine Learning
Python Programming
Automation Scripting
Cloud Platforms
Problem Solving
API Integration
Process Optimization
Data Modeling
Agile Methodologies
Communication Skills
System Design
Robotic Process Automation
Job SummaryWe are looking for a hands-on AI Engineer to design, develop, integrate, and deploy Generative AI, AI chatbot, and Agentic AI solutions. The role will focus on building practical AI applications and integrating LLM capabilities with existing applications, APIs, databases, and enterprise systems.Key ResponsibilitiesDesign and develop AI chatbots, copilots, and LLM-powered applications.Build Agentic AI solutions with reasoning, tool/function calling, multi-step task execution, and workflow automation.Implement RAG, embeddings, vector search, prompt engineering, and conversational memory.Work with commercial and open-source LLMs and select appropriate models based on business and technical requirements.Integrate AI solutions with REST APIs, databases, CRM/ERP systems, and enterprise applications.Develop AI integration services and APIs for existing systems and business workflows.Evaluate and optimize AI solutions for accuracy, reliability, latency, scalability, security, and cost.Collaborate with software engineers, architects, product teams, and business stakeholders.Keep up to date with developments in Generative AI, LLMs, Agentic AI, and AI automation.RequirementsBachelor's degree in Computer Science, AI/ML, Software Engineering, or a related field.3+ years of experience in AI/ML engineering, software engineering, or a related role.Hands-on experience developing LLM applications, AI chatbots, or Generative AI solutions.Practical experience with AI Agents, Agentic AI, tool/function calling, or AI workflow automation.Experience with open-source LLMs such as Llama, Qwen, Mistral, Gemma, or equivalent.Strong Python programming and software engineering skills.Experience with REST APIs, system integration, databases, and cloud/on-premise environments.Hands-on experience with RAG, vector databases, embeddings, and prompt engineering.Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent.Experience with LLM platforms such as OpenAI, Azure OpenAI, Anthropic, Gemini, and/or open-source models.Familiarity with Docker, Git, CI/CD, and production deployment.Preferred SkillsExperience serving open-source LLMs using vLLM, Hugging Face, Ollama, or equivalent.Experience with MCP, multi-agent systems, LLM evaluation/observability, fine-tuning, LoRA/QLoRA, or model optimization.Experience with AWS, Azure, or Google Cloud.Knowledge of AI security, data privacy, access control, and responsible AI.
- Hands-on experience with AI Development fundamentals. Building and testing intelligent systems, from rule-based models to neural networks.
- Large Language Models (LLMs): Explore how LLMs work. Learn how to fine-tune them, evaluate their performance, and integrate them into products and services.
...
Collaboration & Delivery: Work with Product Owner, Developers, Quality Engineers and UX Designers to deliver the Virtual Companion. Contribute to sprint planning, code reviews and documentation.
AI/ML Literacy: A strong grasp of LLM fundamentals, including tokens, temperature, top-p, and context windows.
Prompt Engineering & Evaluation: Design, optimize, and evaluate prompts to improve AI behavior, reasoning, and response quality.
...
Operational Governance: Maintaining operational governance of AI solutions by managing production stability, performance thresholds, compliance requirements, risk controls, and responsible AI practices.
Stakeholder Collaboration: Collaborating with application operations, platform operations, engineering, architecture, and business stakeholders to design, deploy, and continuously improve agent-based solutions.
AI Solution Design: Experience with designing scalable, user-centric AI capabilities that automate workflows and augment decision-making.
...
Assist in developing AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.
Design solutions across generative AI, LLMs, machine learning, computer vision, NLP, intelligent automation, conversational AI, agents and predictive analytics.
Architect enterprise AI platforms across public, private and hybrid cloud, including data platforms, training, fine-tuning, inference, RAG, vector databases, APIs and MLOps/LLMOps.
...
Credit & Risk Intelligence: Lead development of AI/ML models for credit scoring, lease default prediction, and portfolio risk analytics—leveraging both traditional financial data and alternative data sources .
Process Automation: Deploy NLP and generative AI solutions to automate lease document review, contract analysis, and compliance checking; streamline RFP responses and lease negotiation workflows .
Commercial Optimization: Build predictive analytics for lease pricing optimization (NPV/NER modeling), tenant retention scoring, and market intelligence—analyzing comparable properties, pricing trends, and competitive positioning .
...
Assist in developing AI solution architectures, HLD/LLD, data-flow designs, sizing, BoM, costing, implementation roadmaps and proposals for RFI/RFP/tenders.
Design solutions across generative AI, LLMs, machine learning, computer vision, NLP, intelligent automation, conversational AI, agents and predictive analytics.
Architect enterprise AI platforms across public, private and hybrid cloud, including data platforms, training, fine-tuning, inference, RAG, vector databases, APIs and MLOps/LLMOps.
...
Safety & Bias Auditing: Lead "Red Teaming" sessions to identify potential biases, toxic content, or PII (Personally Identifiable Information) leaks.
Regression Testing: Manage the evaluation of model performance across different versions to ensure seamless upgrades and stability.
Collaboration & Delivery: Work with Product Owner, Developers, AI Engineers and UX Designers to deliver the Virtual Companion. Contribute to sprint planning, code reviews and documentation.
...