AI Engineer Role Summary: We are seeking an AI Engineer with a strong background in Generative AI, Natural Language Processing (NLP), Large Language Models (LLMs), and agentic AI to join our growing team. You will focus on building robust, scalable AI solutions that harness Azure AI capabilities, with a strong emphasis on MLOps and LLM frameworks. You should have a passion for crafting high-quality, production-ready AI systems and a proven track record of delivering impactful solutions. Key Responsibilities: * Design & Develop: Architect and implement Generative AI applications using Azure OpenAI Services, Azure Machine Learning, and other Azure AI tools. Develop and fine-tune LLMs for domain-specific tasks using popular frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or similar. Build agentic AI systems capable of autonomous reasoning and task execution. * NLP and Advanced Language Models: Work with Natural Language Processing pipelines, including text classification, summarization, entity extraction, and question answering. * MLOps & Azure Integration: Familiarity with CI/CD pipelines, model versioning, deployment, and monitoring for AI models using Azure Machine Learning MLOps capabilities. Collaborate with DevOps team to ensure seamless integration of models into production systems. * Innovation & Scalability: Stay at the forefront of AI advancements, particularly in LLMs and Generative AI, to continuously enhance our AI solutions. Drive the adoption of best practices for scalable and secure AI system development on Azure. * Mentorship & Collaboration: Provide technical mentorship to junior engineers and contribute to knowledge-sharing within the team. Collaborate closely with cross-functional teams (Product, Engineering) to translate business requirements into technical solutions. Qualifications & Skills: * Experience: Minimum 4 years of experience in AI engineering, with a strong focus on Generative AI, LLMs, and NLP. Proven experience building and deploying AI models using Azure AI capabilities, including Azure OpenAI, Azure ML, and Azure Cognitive Services. Solid experience with LLM frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Hands-on experience with MLOps pipelines and CI/CD practices. * Technical Skills: Proficiency in Python (including libraries like PyTorch, TensorFlow, and popular LLM frameworks). Strong understanding of LLM fine-tuning, prompt engineering, embedding models, and vector databases (e.g., Azure AI Search, Pinecone, Weaviate). Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure, with a preference for Azure. * Soft Skills: Excellent problem-solving skills, with a focus on delivering production-ready solutions. Strong communication and collaboration abilities, with a knack for explaining complex AI concepts to non-technical stakeholders. PS:- This Opportunity is for Gurugram location only.
The Role The implementation consultant will be responsible for leading the end-to-end implementation of HUB for new and existing clients. This includes gathering requirements, understanding data, solution design, configuration, data migration, integration, training, and go-live support . You will work closely with clients to ensure a seamless onboarding experience while collaborating with internal teams across product, engineering, and customer success , with the main goal for delivering value to the customer and supporting their HUB rollout. Accountabilities Engage with client stakeholders (operations, IT, finance) to understand workflows and business objectives. Document functional and technical requirements aligned with best practices. Design solutions leveraging HUB capabilities for NAV oversight, performance management, reporting and post trade. Configure the SaaS platform, ensuring alignment with client requirements. Coordinate internal and client resources to meet implementation goals. Manage data mapping, cleansing, and migration activities. Work with APIs and integration frameworks to connect the platform to market data providers, OMS/EMS, custodians, and other third-party servicer & systems. Conduct end-user training sessions and produce user documentation. Ensure smooth knowledge transfer to client teams. Support user testing and go live process. Provide hypercare and post-go-live support to ensure adoption. Maintain strong client relationships, escalate issues and manage expectations effectively. Deliverables Successful delivery of end-to-end customer go lives Translated stakeholder requirements, including Customer, Design, technology to feed product evolution Contribute to, and drive customer user engagement in delivery process Consistently meet or exceed expectations when evaluated against HUBs core values and technical standards Own your personal continued development About you: Must have Minimum 5+ years’ business analysis or relevant experience Agile experience – working within client implementations Technical experience such as SQL, APIs and integration frameworks Experience working with internal or external customer stakeholders Asset management / financial services experience Proactive, dynamic self-starter who is hands-on and can work across numerous teams in the business A team player, able to work in a collaborative and supportive environment to get things done Someone who can influence decisions, push things along and generally is eager to support moving the product delivery process forward Nice to have. Understanding of integration and functional architecture Knowledge of the Azure cloud stack
Role Summary: We are seeking an AI Engineer with a strong background in Generative AI, Natural Language Processing (NLP), Large Language Models (LLMs), and agentic AI to join our growing team. You will focus on building robust, scalable AI solutions that harness Azure AI capabilities, with a strong emphasis on MLOps and LLM frameworks. You should have a passion for crafting high-quality, production-ready AI systems and a proven track record of delivering impactful solutions. Key Responsibilities: * Design & Develop: Architect and implement Generative AI applications using Azure OpenAI Services, Azure Machine Learning, and other Azure AI tools. Develop and fine-tune LLMs for domain-specific tasks using popular frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or similar. Build agentic AI systems capable of autonomous reasoning and task execution. * NLP and Advanced Language Models: Work with Natural Language Processing pipelines, including text classification, summarization, entity extraction, and question answering. * MLOps & Azure Integration: Familiarity with CI/CD pipelines, model versioning, deployment, and monitoring for AI models using Azure Machine Learning MLOps capabilities. Collaborate with DevOps team to ensure seamless integration of models into production systems. * Innovation & Scalability: Stay at the forefront of AI advancements, particularly in LLMs and Generative AI, to continuously enhance our AI solutions. Drive the adoption of best practices for scalable and secure AI system development on Azure. * Mentorship & Collaboration: Provide technical mentorship to junior engineers and contribute to knowledge-sharing within the team. Collaborate closely with cross-functional teams (Product, Engineering) to translate business requirements into technical solutions. Qualifications & Skills: * Experience: Minimum 4 years of experience in AI engineering, with a strong focus on Generative AI, LLMs, and NLP. Proven experience building and deploying AI models using Azure AI capabilities, including Azure OpenAI, Azure ML, and Azure Cognitive Services. Solid experience with LLM frameworks such as LangChain, LlamaIndex, Hugging Face, etc. Hands-on experience with MLOps pipelines and CI/CD practices. * Technical Skills: Proficiency in Python (including libraries like PyTorch, TensorFlow, and popular LLM frameworks). Strong understanding of LLM fine-tuning, prompt engineering, embedding models, and vector databases (e.g., Azure AI Search, Pinecone, Weaviate). Familiarity with containerization (Docker, Kubernetes) and cloud infrastructure, with a preference for Azure. * Soft Skills: Excellent problem-solving skills, with a focus on delivering production-ready solutions. Strong communication and collaboration abilities, with a knack for explaining complex AI concepts to non-technical stakeholders. Good to have: Experience with backend development, especially in building APIs or integrating AI models into web applications Familiarity with Node.js and related frameworks for developing and deploying scalable backend services. .
The Opportunity Senior Software Engineer is responsible for leading the development and delivery of feature sets according to the product road map. The Sr. Software Engineer works closely with the product owners, architects and other engineers to come up with the optimal low level implementations, which is in line with HUBs internal standards and reference architecture guidelines. You will also mentor other engineers in the team to write the highest quality code, while being the Remember, this is a greenfield project - the only legacy that exists will be the one you create! You’ll be responsible for… · Implementing and delivering the products’ feature set with the highest quality, limiting technical debt where possible · Understanding the pros and cons of complex architecture patterns and translating these into technical implementations · Maintaining a high level of User Story hygiene including estimation and status updates · Keeping up to date with the latest technology trends and releases · Mentoring other Engineers and doing code reviews · Participating in hiring activities across the firm · Delivering in scenarios where you may not agree with every design decision · Being curious – never be afraid to ask questions About you Must have: · 5+ years writing core Java in any environment (Large Enterprise, SME, or Start-up), including modern Java like Streams, Lambda Expressions and Functional Programming. · Experience building high volume, distributed systems · Experience with Spring Boot, RESTful APIs and AVRO/gRPC · Familiarity with event driven technologies (Kafka, Event Buses, etc…) · Experience working with CI/CD pipelines with one of: Jenkins, GitLab CI, GitHub Actions, Azure DevOps Pipelines · Familiarity with at least one major public cloud provider (AWS, Azure or GCP) · Comfortable working in an Agile environment where iterative development and regular demos are the norm · A natural problem solver Nice to have: · Familiarity with a multitude of microservice architecture patterns (Sidecar, Ambassador, Anti-corruption layer, Gateway Routing, BFF etc…) · Experience with big data & real time analytics particularly with distributed datasets and large volumes in a Data Warehouse · Experience with container orchestration tools such as Kubernetes as well as docker · Experience with stream processing technologies (Spark, Flink, etc...) · Familiar with Web 3.0 concepts, Distributed ledger technologies, etc. · Asset management domain experience, for e.g. post trade, reference data, etc.
The Role The implementation consultant will be responsible for leading the end-to-end implementation of HUB for new and existing clients. This includes gathering requirements, understanding data, solution design, configuration, data migration, integration, training, and go-live support . You will work closely with clients to ensure a seamless onboarding experience while collaborating with internal teams across product, engineering, and customer success , with the main goal for delivering value to the customer and supporting their HUB rollout. Accountabilities Engage with client stakeholders (operations, IT, finance) to understand workflows and business objectives. Document functional and technical requirements aligned with best practices. Design solutions leveraging HUB capabilities for NAV oversight, performance management, reporting and post trade. Configure the SaaS platform, ensuring alignment with client requirements. Coordinate internal and client resources to meet implementation goals. Manage data mapping, cleansing, and migration activities. Work with APIs and integration frameworks to connect the platform to market data providers, OMS/EMS, custodians, and other third-party service & systems. Conduct end-user training sessions and produce user documentation. Ensure smooth knowledge transfer to client teams. Support user testing and go live process. Provide hypercare and post-go-live support to ensure adoption. Maintain strong client relationships, escalate issues and manage expectations effectively. Deliverables Successful delivery of end-to-end customer go lives Translated stakeholder requirements, including Customer, Design, technology to feed product evolution Contribute to, and drive customer user engagement in delivery process Consistently meet or exceed expectations when evaluated against HUBs core values and technical standards Own your personal continued development About you: Must have Minimum 5+ years’ business analysis or relevant experience Agile experience – working within client implementations Technical experience such as SQL, APIs and integration frameworks Experience working with internal or external customer stakeholders Asset management/Hedge Fund / financial services experience Proactive, dynamic self-starter who is hands-on and can work across numerous teams in the business A team player, able to work in a collaborative and supportive environment to get things done Someone who can influence decisions, push things along and generally is eager to support moving the product delivery process forward Nice to have. Understanding of integration and functional architecture Knowledge of the Azure cloud stack
Role Summary We are seeking a Full-Stack AI Engineer with strong hands-on experience in Generative AI, agentic AI systems, and modern web/backend development . This role is perfect for someone who loves to blend AI capabilities with full-stack engineering , building end-to-end GenAI-powered applications that run in production. You’ll work with Azure AI ecosystem (Azure OpenAI, Azure ML, Cognitive Services) and agentic frameworks (LangChain, LlamaIndex, Hugging Face) while also designing scalable APIs, UIs, and integration layers. You should think like a builder —comfortable with both coding products and orchestrating AI agents , not just tweaking ML models. Key Responsibilities 1. AI Applications & Agentic Systems Design and develop GenAI-powered applications using Azure OpenAI, Azure Cognitive Services, and LangChain/LlamaIndex. Build multi-agent architectures for autonomous reasoning, workflow automation, and integrations with enterprise systems. Implement RAG pipelines with embeddings, vector databases (Azure AI Search, Pinecone, Weaviate), and APIs. 2. Full-Stack Development Build backend services and APIs (Python FastAPI / Node.js / Express) to integrate GenAI features into applications. Develop frontend components (React/Next.js, TypeScript) to deliver user-facing AI-powered experiences. Apply best practices in scalable backend systems, event-driven design, and API-first development . 3. Azure Deployment Deploy and manage AI services on Azure AI Foundry, Azure Functions, Kubernetes . Set up CI/CD pipelines , model/service versioning, and monitoring. Ensure production systems are secure, performant, and cost-optimized . 4. Collaboration & Impact Work closely with Product & Engineering teams to translate business use cases into AI-driven features. Provide mentorship to junior engineers on full-stack + GenAI integration. Stay updated on LLM frameworks, orchestration tools, and multi-agent systems . Qualifications & Skills Experience: 4–7 years in software engineering, with at least 2 years in Generative AI / LLM applications . Proven track record in full-stack development (React/Next.js, Node.js, Python). Hands-on experience with Azure AI (OpenAI, Cognitive Search, Azure ML) . Technical Skills: Frontend: React/Next.js, TypeScript, Tailwind (or similar). Backend: Python (FastAPI, Flask), Node.js/Express. GenAI: Prompt engineering, embeddings, vector DBs, RAG pipelines, agentic design. Cloud & Infra: Azure services, Docker, Kubernetes, CI/CD pipelines. Soft Skills: Strong problem-solving with a product-builder mindset . Ability to explain GenAI solutions clearly to both technical and business stakeholders. Comfortable in a startup culture (fast-moving, ownership-driven). Why Join Us? Work on cutting-edge agentic AI applications with real-world impact in fintech & enterprise ops. Be part of a fast-growing AI startup where you own features end-to-end. Learn and build at the intersection of GenAI + full-stack development .
As a Full-Stack AI Engineer at the company, you will have the exciting opportunity to work on cutting-edge AI applications with real-world impact in fintech and enterprise operations. You will be responsible for designing and developing GenAI-powered applications using Azure AI ecosystem and agentic frameworks, while also focusing on full-stack development and Azure deployment. Your role will involve collaborating with cross-functional teams, providing mentorship, and staying updated on the latest frameworks and tools in the GenAI space. **Key Responsibilities:** - Design and develop GenAI-powered applications using Azure OpenAI, Azure Cognitive Services, and LangChain/LlamaIndex. - Build multi-agent architectures for autonomous reasoning, workflow automation, and integrations with enterprise systems. - Implement RAG pipelines with embeddings, vector databases (Azure AI Search, Pinecone, Weaviate), and APIs. - Build backend services and APIs (Python FastAPI / Node.js / Express) to integrate GenAI features into applications. - Develop frontend components (React/Next.js, TypeScript) to deliver user-facing AI-powered experiences. - Deploy and manage AI services on Azure AI Foundry, Azure Functions, Kubernetes. - Work closely with Product & Engineering teams to translate business use cases into AI-driven features. - Provide mentorship to junior engineers on full-stack + GenAI integration. - Stay updated on LLM frameworks, orchestration tools, and multi-agent systems. **Qualifications & Skills:** - **Experience:** - 4-7 years in software engineering, with at least 2 years in Generative AI / LLM applications. - Proven track record in full-stack development (React/Next.js, Node.js, Python). - Hands-on experience with Azure AI (OpenAI, Cognitive Search, Azure ML). - **Technical Skills:** - Frontend: React/Next.js, TypeScript, Tailwind (or similar). - Backend: Python (FastAPI, Flask), Node.js/Express. - GenAI: Prompt engineering, embeddings, vector DBs, RAG pipelines, agentic design. - Cloud & Infra: Azure services, Docker, Kubernetes, CI/CD pipelines. - **Soft Skills:** - Strong problem-solving with a product-builder mindset. - Ability to explain GenAI solutions clearly to both technical and business stakeholders. - Comfortable in a startup culture (fast-moving, ownership-driven).,
Company Description HUB provides SaaS solutions that help asset managers and hedge funds simplify daily tasks by automating complex and manual processes; seamlessly integrating investment data directly into operational workflows. HUB products streamline manual processes, reduce operational risk, expand data access and drive growth. HUB is committed to providing customers with flexible adoption, quick onboarding, rapid ROI, and scalable growth aligned with their business needs. Website https://www.hub.com/ The Opportunity We are seeking a highly skilled and motivated Senior Azure Platform & DevOps Engineer to lead the design, automation, and management of scalable, secure, and cost-optimized cloud infrastructure on Microsoft Azure. This role blends deep expertise in Azure infrastructure engineering, DevOps practices, and platform reliability—with a strong focus on Kubernetes, CI/CD, and event-driven architectures. Key Responsibilities 🔧 Azure Infrastructure & Platform Engineering (60%) · Architect, deploy, and manage Azure cloud infrastructure using Terraform, Bicep, and ARM templates. · Build secure, scalable, and highly available solutions aligned with architectural best practices. · Manage Azure networking, identity, RBAC, and ensure compliance with SOC 2, NIST, and internal governance frameworks. · Implement cost optimization, backup/recovery, and business continuity strategies. · Maintain and support Kafka clusters (Apache Kafka or Confluent) for event-driven systems. 🚀 DevOps, Automation & Containerization (40%) · Develop and maintain CI/CD pipelines using Azure DevOps, GitHub Actions, or Argo CD. · Automate infrastructure provisioning and operations using Linux, PowerShell, Python, Bash, or Golang. · Implement GitOps workflows and automate Kubernetes deployments using Argo CD or Flux. · Manage containerized workloads on Azure Kubernetes Service (AKS), including scaling, monitoring, and troubleshooting. · Collaborate closely with development teams to ensure smooth deployments and platform reliability. Required Skills & Experience · 8+ years of experience in cloud infrastructure and DevOps engineering, with a strong Azure focus. · Strong communication skills to explain complex technical concepts to stakeholders. · Hands-on expertise with Azure IaaS/PaaS, networking, identity, and security. · Proficiency in Infrastructure as Code (Terraform, Bicep, ARM). · Experience managing Kubernetes (AKS) in production environments and deploying with Helm and Argo CD. · Scripting skills in Linux, PowerShell, Python, or Golang. · Experience with Kafka or Confluent platforms. · Solid understanding of CI/CD pipelines, monitoring, logging, and alerting tools (Azure Monitor, Prometheus). · Knowledge of cloud governance, cost management, and security best practices. Preferred Qualifications · Bachelor’s degree in Computer Science, IT, or related field. · Certifications such as Microsoft Azure (AZ-104, AZ-305) or Kubernetes (CKA). Why HUB? · Work with cutting-edge technologies and a passionate team. · Flexible work arrangements and a culture of trust. · Opportunities for growth, learning, and leadership. · Be part of a company that values innovation, integrity, and impact. PS:- This position is for Gurugram Location.