Prompt Engineer Jobs in Chennai.
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Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide.
Living our values everyday results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves.
Job Title: AI Applications Engineer II
Location: Bangalore/ Chennai, India
About the Role
We’re looking for a passionate AI Applications Engineer II to join our growing Enterprise AI Team. In this role, you’ll help manage, support, and optimize our Google Gemini Enterprise agentic AI platform, ensuring it operates securely, efficiently, and at scale across the organization.
You’ll spend most of your time focused on Gemini Enterprise platform administration, governance, and support, along with some dedicated time to enhancing/building/doing POC work on agentic and automation projects that furthers performance, user experience, and integration with Five9 enterprise systems.
If you’re driven by innovation, precision, and the opportunity to shape how AI supports a global business, this is the role for you.
Key Responsibilities
- Administer, configure, and optimize Gemini Enterprise and related AI agentic functionality to ensure seamless performance and compliance within Five9 environments.
- Manage user provisioning, license assignments, access controls, and security policies, ensuring consistency with IT, Infosec and compliance governance standards.
- Oversee appropriate Google Cloud Platform (GCP) resources — including Project services, AI/ML engine, storage, and Gemini AI models — focusing on reliability, performance, and cost management.
- Support cloud run workflows, CI/CD automation pipelines, and containerized environments, leveraging tools such as Terraform, Docker, and Kubernetes.
- Partner with data engineers, DevOps teams, and business stakeholders to troubleshoot issues, implement updates, and ensure timely support for production workloads.
- Conduct prompt engineering and workflow optimization to improve agentic AI accuracy, responsiveness, and relevance.
- Maintain and update documentation, runbooks, and best practice guides for platform operations, deployment, and support.
- Deliver training and enablement sessions to end users and power users on Gemini Enterprise capabilities and AI use cases.
- Continuously evaluate emerging Google AI and Gemini agentic technologies, recommending improvements that enhance scalability and automation.
Key Requirements
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field (AI or data systems focus preferred).
- Minimum of 3 years of GCP experience supporting or developing AI/ML solutions on Google platform.
- Hands on experience with AI/ ML solutions/apps and operational best practices (ML Ops experience is advantageous).
- Proficiency with GCP services such as Compute Engine, IAM, Kubernetes, VPC, BQ, etc.
- Experience in automation and scripting using Python, Bash, and Infrastructure as Code (IaC) tools such as Terraform or Deployment Manager.
- Familiarity with Gemini Enterprise or similar enterprise AI frameworks, including prompt engineering, AI agent configuration, and data governance.
- Strong understanding of security, compliance, and auditing practices, including DLP, Access Transparency, and data residency standards.
- Excellent problem-solving, analytical, and troubleshooting skills.
- Strong interpersonal and communication abilities, with the capacity to explain technical topics to non-technical audiences.
- A passion for innovation, continuous learning, and driving impactful AI adoption across the enterprise.
Why You’ll Love Working Here
- Be part of a forward-thinking Enterprise AI Team, driving next-generation innovation across the company.
- Work hands-on with cutting-edge technologies like Google Gemini Enterprise and other agentic AI tools that power real-world business applications.
- Collaborate with skilled engineers, data scientists, and business leaders on high-visibility projects that make a measurable impact.
- Enjoy a culture that values experimentation, continuous learning, and teamwork, with opportunities to grow your skills in cloud operations and AI engineering.
- Play a key role in transforming enterprise workflows through AI innovation, scalability, and operational excellence.
Five9 embraces diversity and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we are. Five9 is an equal opportunity employer.
View our privacy policy, including our privacy notice to California residents here: https://www.five9.com/pt-pt/legal.
Note: Five9 will never request that an applicant send money as a prerequisite for commencing employment with Five9.
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Gen AI Lead
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Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
Role: GenAI Lead Engineer
Experience: 8+ years total (with significant hands-on GenAI / LLM work)
Job Overview:
We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.
Key Responsibilities:
- Technical Leadership:
- Lead the end-to-end design and implementation of Generative AI solutions.
- Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
- Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
- Solution Development:
- Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
- Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
- Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
- Ensure scalability, performance, and security of AI solutions deployed in production.
- Integration and Deployment:
- API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
- Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
- Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
- Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
- Data Strategy and Preparation:
- Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
- Implement data governance and privacy practices in line with organizational policies.
- Innovation and Research:
- Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
- Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
- Stakeholder Collaboration:
- Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
- Present technical concepts, project progress, and AI capabilities to non-technical audiences.
Key Requirements
- Technical Skills:
- Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
- Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
- Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
- Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
- Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
- Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
- Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
- Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
- 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
- Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
- Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
- Proven track record of leading AI projects from inception to production.
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
- Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
Candidate Privacy Policy
Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, “Orion,” “we” or “us”) are committed to protecting your privacy. This Candidate Privacy Policy (orioninc.com) (“Notice”) explains:
- What information we collect during our application and recruitment process and why we collect it;
- How we handle that information; and
- How to access and update that information.
Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.
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Applied AI Engineer - MCP
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Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together.
About the Team At Business Technology, we use Appian to run Appian. We are launching our first internal AI team to build the foundation for how our global company works. This team won't just use AI, they will build the brain of the enterprise, spanning everything from predictive intelligence in our data warehouse to the GenAI infrastructure that powers our internal autonomous agents.
We are hiring a founding group of engineers to kickstart this mission. As an AI Engineer on this team, you won’t be maintaining legacy systems; you’ll be building from the ground up. You will own the full spectrum of AI: crafting predictive ML models to find insights in our data warehouse and architecting GenAI systems that allow any employee to interact with enterprise knowledge through intelligent agents.
If you want to be part of the original team that defines internal AI for a leading automation company, this is your moment.
PLEASE NOTE: This is a midlevel role and is aimed at people with 3+ years experience
What you’ll do:
- Build the AI Platform: Design, deploy, and scale GenAI infrastructure on GCP Vertex AI (preferred) or AWS Bedrock.
- Build & Operate MCP Servers: Develop and maintain Model Context Protocol (MCP) servers that expose enterprise systems (databases, APIs, internal tools) as structured, AI-consumable capabilities.
- Design the Tool Layer: Build the tool registry and invocation framework that allows agents to interact with internal systems safely and reliably including schema design, access controls, and error handling.
- Engineer Agent-to-Agent Infrastructure: Architect the communication and coordination layer that allows specialized agents to delegate tasks, share context, and compose into larger autonomous workflows.
- Own the Retrieval Layer: Architect and operate RAG systems, including vector stores, embedding pipelines, chunking strategies, and retrieval evaluation frameworks.
- Establish AI Reliability: Instrument AI systems with logging, tracing, latency monitoring, and evaluation hooks so agents can be trusted, debugged, and improved in production.
Required Qualifications:
- AI Infrastructure Experience: Professional experience building and deploying production-grade GenAI systems on GCP Vertex AI or AWS Bedrock including LLM APIs, agent frameworks, and RAG pipelines.
- Python Mastery: Deep proficiency in Python and common AI/ML libraries (e.g., LangChain, LlamaIndex, OpenAI SDK, Google Cloud AI SDK).
- Agentic Systems: Hands-on experience building multi-step, tool-calling AI agents that operate reliably in production including tool schema design, structured outputs, and failure handling.
- MCP or Tool Protocol Experience: Familiarity with Model Context Protocol (MCP) or equivalent patterns for exposing enterprise resources to AI systems as callable, permissioned tools.
- Vector & Retrieval Systems: Experience with vector databases (Pinecone, pgvector, or similar) and embedding-based retrieval at scale.
- Technical Foundation: B.S. in Computer Science, Engineering, or a related technical field.
- The Pioneer Mindset: A self-starter who is excited to be part of a "first-of-its-kind" team and thrives in environments where you are building the playbook.
Preferred Qualifications:
- Multi-Agent Architectures: Experience designing orchestrator/subagent patterns, agent handoff protocols, or systems where multiple AI models coordinate to complete complex tasks (e.g., using frameworks like LangGraph, CrewAI, or AutoGen).
- AI Observability: Experience with LLM evaluation frameworks, prompt regression testing, or agent trace monitoring (e.g. custom eval pipelines).
- Data Warehouse Integration: Familiarity with SQL and pulling data from Snowflake or BigQuery to ground AI agents in live business context.
- Appian Exposure: Experience with the Appian platform or interest in integrating AI agents into low-code automation workflows.
- Predictive ML (Nice to Have): Some familiarity with ML fundamentals is a plus, but not a focus of this role.
This role is based at our Chennai office in Brigade World Trade Center Chennai. Appian was built on a culture of in-person collaboration, which we believe is a key driver of our mission to be the best. Employees hired for this position are expected to be in the office 5 days a week to foster that culture and ensure we continue to thrive through shared ideas and teamwork. We believe being in the office provides more opportunities to come together and celebrate working with the exceptional people across Appian.
Tools and Resources
- Training and Development: During onboarding, we focus on equipping new hires with the skills and knowledge for success through department-specific training. Continuous learning is a central focus at Appian, with dedicated mentorship and the First-Friend program being widely utilized resources for new hires.
- Growth Opportunities: Appian provides a diverse array of growth and development opportunities, including our leadership program tailored for new and aspiring managers, a comprehensive library of specialized department training through Appian University, skills based training, and tuition reimbursement for those aiming to advance their education. This commitment ensures that employees have access to a holistic range of development opportunities.
- Community: We’ll immerse you into our community rooted in respect starting on day one. Appian fosters inclusivity through our 8 employee-led affinity groups. These groups help employees build stronger internal and external networks by planning social, educational, and outreach activities to connect with Appianites and larger initiatives throughout the company.
Benefits
Appian offers a comprehensive benefits package designed to support your health, wellbeing, and financial future. Benefits may include health coverage, Employee Assistance Program (EAP) with free mental health support, life and disability insurance, an Employee Stock Purchase Program (ESPP), a retirement/pension plan, wellness dollars, tuition reimbursement, family-forming benefits and more. Benefits vary by country—please ask your Talent Acquisition contact for details specific to the location you are applying to.
About Appian
Appian provides process automation technology. We automate complex processes in large enterprises and governments. Our platform is known for its unique reliability and scale. We’ve been automating processes for 25 years and understand enterprise operations like no one else. For more information, visit appian.com. [Nasdaq: APPN]
Follow Appian: LinkedIn, Youtube, Instagram, Facebook
Appian is an equal opportunity employer that strives to attract and retain the best talent. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law.
Appian provides reasonable accommodations to applicants in accordance with all applicable laws. If you need a reasonable accommodation for any part of the employment process, please contact us by email at ReasonableAccommodations@appian.com. Please note that only inquiries concerning a request for reasonable accommodation will be responded to from this email address.
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About Us
“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery.
WHY JOIN CAPCO?
You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.
MAKE AN IMPACT
Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.
#BEYOURSELFATWORK
Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.
CAREER ADVANCEMENT
With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.
DIVERSITY & INCLUSION
We believe that diversity of people and perspective gives us a competitive advantage.
Job Description:
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Role Description:
Hands-on engineer delivering Finance EUC automations on IT-governed platforms. Understands demand for automation, detailed requirements, and undertakes build & test, production deployment activities and RTB change implementation, following defined standards and platform guardrails. Contributes to opportunity scoping by providing technical input on feasibility and effort. Produces code, documentation and test evidence aligned to agreed closure criteria, and supports controlled deployment and post-release fixes. Works closely with the POD Lead, Finance Domain BA and platform support to ensure solutions are reliable and supportable.
Skills / Knowledge / Experience:
- Strong understanding of Python programming with Excel dependent and Pandas library, and capable of debugging Python code
- Strong data preparation, visualization, and analytics capability
- Design and deliver AI-assisted remediation capabilities
- Strong understanding of EUCs (End User Computing) and their remediation through AI
- Experience with Gen-AI tools and prompt engineering
- Skilled in IT-managed automation platforms e.g., Alteryx
- Knowledge of Finance data systems
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Apply to CapcoAbout DevRev
At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries.
About the Role:
As a Forward Deployed Engineer at DevRev, you will work closely with our pre- and post-sales Customer Experience team by developing solutions over the core platform via applications written in TypeScript, JavaScript, Python, etc. One of the key functions of this role is, building the Knowledge Graph that includes integration of DevRev with other SaaS and non-SaaS systems through webhooks and APIs and/ or real-time communication architectures. You will be expected to employ your creativity and expertise to ideate and shape how AI, analytics and workflows are used in customers' processes.
What You'll Do:
- Customer-facing: 30% working directly with customers.
- Coding & Integration: 70-80% hands-on technical implementation
- Build & Deploy Solutions: Design, develop, and launch AI agents, integrations, and automations that connect DevRev with customers' existing tech stacks and workflows.
- Integrate Systems: Connect DevRev with SaaS and non-SaaS platforms through APIs, webhooks, and real-time communication architectures for seamless data flow.
- Optimize AI Performance: Apply prompt engineering, fine-tune semantic search engines, and leverage generative AI techniques to enhance agent accuracy and user experience.
- Own Data Insights: Write SQL queries, perform data analysis, and build dashboards to surface insights that drive customer decision-making.
- Prototype & Iterate: Develop rapid proofs-of-concept, conduct live technical demos, and refine solutions based on customer and stakeholder feedback.
- Lead Cross-functional Collaboration: Maintain constant communication loops with customers, engineering, product, customer success, support, and revenue teams to ensure alignment.
- Guide Technical Adoption: Learn and master new tools, then guide customers through critical workflows like code repository integrations and advanced configurations.
- Travel Ready: Willingness to travel up to 30% for on-site implementations, technical workshops, and customer engagements.
What You Bring:
- Experience: 5+ years in software development, systems integration, or platform engineering. Customer-facing experience is a plus.
- Background: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- Coding Skills: Strong proficiency in TypeScript/JavaScript, Python, data structures and algorithms. (Nice to have: Go)
- Applied AI Knowledge: Familiarity with large language models (LLMs), prompt engineering, frameworks like RAG and function calling, and building evals to validate agentic AI solutions.
- Integration Expertise: Deep experience with large-scale data synchronization (one-way and two-way), API integration patterns (REST, GraphQL, webhooks), and event-driven/pub/sub architectures.
- Cloud & Deployment: Hands-on experience deploying on serverless and edge platforms (AWS Lambda, Google Cloud Functions) with modern DevOps practices (CI/CD, containers, observability).
- Data Transformation: Skilled in data mapping, schema alignment, and working with heterogeneous systems. Understanding of data modeling and graph data structures.
- Observability: Experience implementing clear logging, actionable error surfacing, and telemetry to support faster debugging and issue resolution.
- Context-Aware Systems: Familiarity with Model Context Programming (MCP) for building adaptive, context-aware integrations.
- Problem-Solving: Strong track record triaging and unblocking both technical and non-technical blockers to keep projects moving forward.
- Documentation: Experience writing concise, well-structured documentation that supports long-term team understanding and seamless onboarding.
- Communication: Strong written and verbal skills to articulate technical concepts to engineers, product teams, and business stakeholders.
As part of our hiring process, shortlisted candidates will undergo a Background Verification (BGV). By applying, you consent to sharing personal information required for this process. Any offer made will be subject to successful completion of the BGV.
DevRev is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
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Gen AI Lead
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Role: GenAI Lead Engineer
Experience: 8+ years total (with significant hands-on GenAI / LLM work)
Job Overview:
We are seeking an innovative and highly skilled Lead Generative AI (GenAI) Engineer to spearhead the design, development, and deployment of advanced AI-powered solutions. In this role, you will lead a team of engineers and data scientists to harness cutting-edge Generative AI technologies and implement them to solve complex business problems, enhance user experiences, and drive innovation. This role combines deep technical expertise, leadership, and a strong understanding of AI trends and tools.
Key Responsibilities:
- Technical Leadership:
- Lead the end-to-end design and implementation of Generative AI solutions.
- Provide technical guidance and mentorship to engineers and data scientists working on GenAI projects.
- Stay updated with the latest trends, research, and advancements in Generative AI and Large Language Models (LLMs).
- Solution Development:
- Architect, train, and fine-tune state-of-the-art LLMs and generative AI models
- Develop and optimize pipelines for prompt engineering, retrieval-augmented generation (RAG), and domain-specific fine-tuning.
- Develop and deploy generative AI models, particularly focusing on ChatGPT, using Python on Azure or AWS Platform or .Net on Azure platform
- Ensure scalability, performance, and security of AI solutions deployed in production.
- Integration and Deployment:
- API Development: Ability to define and deliver API access for GenAI services, facilitating integration with other systems and applications.
- Collaborate with software engineering teams to integrate GenAI solutions into enterprise applications and services.
- Utilize cloud platforms (e.g., Azure, AWS, or GCP) to deploy and manage AI models and APIs.
- Leverage MLOps practices for continuous model monitoring, retraining, and improvement.
- Data Strategy and Preparation:
- Collaborate with data engineering teams to ensure high-quality data acquisition, preprocessing, and augmentation for model training and fine-tuning.
- Implement data governance and privacy practices in line with organizational policies.
- Innovation and Research:
- Experiment with new generative AI techniques, such as multimodal AI, reinforcement learning with human feedback (RLHF), and active learning.
- Evaluate and recommend AI frameworks, libraries, and platforms for project requirements.
- Stakeholder Collaboration:
- Work closely with product managers, business stakeholders, and UX designers to define AI-powered product features and use cases.
- Present technical concepts, project progress, and AI capabilities to non-technical audiences.
Key Requirements
- Technical Skills:
- Hands-on experience with cloud platforms and services for AI/ML, such as Azure AI Services, Azure Machine Learning, AWS Bedrock, or Google Vertex AI.
- Hands on experience in any of LLMs such as OpenAI’s ChatGPT Models , Gemini, Llama 2 ,Claude 2 ,Grok
- Hands on experience in any of the agentic frameworks like LangChain, Semantic kernel, AutoGen, CrewAi
- Hands on experience using any of vector database like Chroma, Pinecone, Weaviate, Faiss
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF)
- Strong expertise in LLMs and generative AI frameworks like OpenAI, Hugging Face Transformers, or similar platforms.
- Deep understanding of natural language processing (NLP) concepts, including tokenization, embeddings, and sequence-to-sequence models.
- Proficiency in Python and libraries such as TensorFlow, PyTorch, and Scikit-learn.
- Experience in CI/CD pipeline management and automation tools, particularly within the Azure DevOps environment. Knowledge of containerization (e.g., Docker) and orchestration tools is also important
- Familiarity with MLOps tools and practices, such as MLflow, Kubeflow, or Docker.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field (Ph.D. preferred).
- 8+ years of experience in AI/ML engineering, with 2+ years specifically in Generative AI.
- Minimum of 2 years of experience in building Conversational AI applications using cloud-based services and in orchestrating AI/ML services for building a complete solution
- Minimum of 6 years of extensive full-time experience in Data Analysis, Statistics, Machine Learning, or Computer Science
- Proven track record of leading AI projects from inception to production.
- Experience with multimodal AI and advanced techniques like Tree-of-Thoughts, Retrieval-Augmented Generation (RAG), or Reinforcement Learning with Human Feedback (RLHF).
- Certifications in AI/ML or cloud platforms (e.g., Azure AI Engineer, AWS Certified Machine Learning).
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Apply to Orion Innovation Naukri