17 Haystack Jobs

You will be responsible for designing, developing, and scaling the AI Agent Framework that powers automation-first modules in RevAi Pro, such as Tell Me, Action Center, and intelligent AI agents. This role is critical to shaping the core foundation of how automation, enterprise search, and just-in-time execution work inside our platform. Architect and implement the core orchestration engine for AI agents (event-driven/task-based). Manage agent lifecycle functions such as spawn, pause, escalate, and terminate. Enable secure, real-time communication between agents, services, and workflows. Integrate memory and retrieval systems using vector databases like Pinecone, Weaviate, or Qdrant. Integrate LLM providers (OpenAI, Azure OpenAI, Anthropic, Mistral, etc.) into agent workflows. Create modular prompt templates with retry/fallback mechanisms. Implement chaining logic and dynamic tool use for agents using LangChain or LlamaIndex. Develop reusable agent types such as Summarizer, Validator, Notifier, Planner, etc. Develop FastAPI-based microservices for agent orchestration and skill execution. Create APIs to register agents, execute agent actions, and manage runtime memory. Implement RBAC, rate limiting, and security protocols for multi-tenant deployments. Build connectors to integrate structured (CRM, SQL) and unstructured data sources (email, docs, transcripts). Route incoming data streams to relevant agents based on workflow and business rules. Support ingestion from tools like Salesforce, HubSpot, Gong, and Zoom. Deploy the agent platform using Docker and Kubernetes on Azure. Implement Redis, Celery, or equivalent async task systems for agent task queues. Set up observability to monitor agent usage, task success/failure, latency, and hallucination rates. Create CI/CD pipelines for agent modules and prompt updates. Ideal Candidate Profile: - 2-4 years of experience in backend engineering, ML engineering, or agent orchestration. - Strong command over Python (FastAPI, asyncio, Celery, SQLAlchemy). - Experience with LangChain, LlamaIndex, Haystack, or other orchestration libraries. - Hands-on with OpenAI, Anthropic, or similar LLM APIs. - Comfortable with vector embeddings and semantic search systems. - Understanding of modern AI agent frameworks like AutoGen, CrewAI, Semantic Planner, or ReAct. - Familiarity with multi-tenant API security and SaaS architecture. - Bonus: Frontend collaboration experience to support UI for agents and dashboards. - Bonus: Familiarity with SaaS platforms in B2B domains like RevOps, CRM, or workflow automation. What You'll Gain: - Ownership of agent architecture inside a live enterprise-grade AI platform. - Opportunity to shape the future of AI-first business applications. - Collaboration with founders, product leaders, and early enterprise customers. - Competitive salary with potential ESOP. - First-mover engineering credit on one of the most advanced automation stacks in SaaS.,

Must Have Skills: 2+ years of hands-on experience in agentic AI / multi-agent systems. Proficiency with LangChain, Langraph, CrewAI, AutoGen, Haystack, or equivalent frameworks. Strong background in Python and experience with prompt engineering, tools integration, and chaining logic. Solid understanding of LLM APIs, RAG, vector stores, tool use, and memory architectures. Hands-on experience with open-source and commercial LLMs (e.g., GPT-4, Claude, Gemini, Mistral). Experience deploying AI agents in cloud-native environments (AWS, GCP, Azure). Ability to lead architectural discussions, PoCs, and hands-on development in fast-paced environments. Model-cost profiling and budgeting (API call minimization, batch vs. streaming) Latency tuning for real-time agents, Autoscaling strategies." Exposure to Autonomous AI agents (AutoGPT, BabyAGI, CAMEL, MetaGPT). Understanding of LLM fine-tuning, adapters, and RLHF. Experience with agent simulation, environment modeling, or reinforcement learning is a plus. Familiarity with compliance, privacy, and safety in GenAI deployments. Prior experience in building domain-specific agents (Lifescience, healthcare, Pharma). Key Responsibilities: Architect and implement agentic AI systems using modern LLM orchestration frameworks (LangChain, CrewAI, AutoGen, etc.). Design multi-agent collaboration models including planner-solver, autonomous teams, and goal decomposition agents. Build reusable tooling, APIs, and memory architectures for agent interaction, coordination, and context persistence. Lead hands-on development and deployment of GenAI applications (e.g., assistants, copilots, decision support). Evaluate and integrate LLMs (OpenAI, Claude, Mistral, LLaMA, etc.), vector databases (Pinecone, Weaviate, FAISS), and retrieval systems (RAG). Optimize agent performance for real-time environments, reliability, scalability, and ethical constraints. Guide teams in adopting agent frameworks, best practices, prompt engineering, and model fine-tuning. Collaborate with stakeholders to translate business requirements into technical solutions using agent-based paradigms. Continuously monitor trends in multi-agent systems, cognitive architectures, and open-source AI frameworks.

We are searching for a skilled and adaptable Data Engineer with proficiency in PySpark, Apache Spark, and Databricks, combined with knowledge in analytics, data modeling, and Generative AI/Agentic AI solutions. This position suits individuals who excel at the convergence of data engineering, AI systems, and business insights, contributing to impactful programs with clients. Your responsibilities will include designing, constructing, and enhancing distributed data pipelines utilizing PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. You will also be tasked with supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications. Additionally, creating and maintaining interactive dashboards and BI reports using tools like Power BI, Tableau, or Looker for business stakeholders and consultants will be part of your role. Furthermore, your duties will involve conducting adhoc data analysis to facilitate data-driven decision-making and rapid insight generation. You will be expected to develop and sustain robust data warehouse schemas, star/snowflake models, and provide support for data lake architecture. Integration with and support for LLM agent frameworks like LangChain, LlamaIndex, Haystack, or CrewAI for intelligent workflow automation will also fall under your purview. In addition, ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments (Azure/AWS/GCP) will be important aspects of your work. Collaboration with cross-functional teams, including AI scientists, analysts, and business teams to drive use-case delivery, is key. Lastly, maintaining robust data governance, lineage, and metadata management practices using tools such as Azure Purview or DataHub will also be part of your responsibilities.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

We are looking for a highly motivated Mid-Level AI Engineer to join our growing AI team. Your main responsibility will be to develop intelligent applications using Python, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG) systems. Working closely with data scientists, backend engineers, and product teams, you will build and deploy AI-powered solutions that provide real-world value. Your key responsibilities will include designing, developing, and optimizing applications utilizing LLMs such as GPT, LLaMA, and Claude. You will also be tasked with implementing RAG pipelines to improve LLM performance using domain-specific knowledge bases and search tools. Developing and maintaining robust Python codebases for AI-driven solutions will be a crucial part of your role. Additionally, integrating vector databases like Pinecone, Weaviate, and FAISS, as well as embedding models for information retrieval, will be part of your daily tasks. You will work with APIs, frameworks like LangChain and Haystack, and various tools to create scalable AI workflows. Collaboration with product and design teams to define AI use cases and deliver impactful features will also be a significant aspect of your job. Conducting experiments to assess model performance, retrieval relevance, and system latency will be essential for continuous improvement. Staying up-to-date with the latest research and advancements in LLMs, RAG, and AI infrastructure is crucial for this role. To be successful in this position, you should have at least 3-5 years of experience in software engineering or AI/ML engineering, with a strong proficiency in Python. Experience working with LLMs such as OpenAI and Hugging Face Transformers is required, along with hands-on experience in RAG architecture and vector-based retrieval techniques. Familiarity with embedding models like SentenceTransformers and OpenAI embeddings is also necessary. Knowledge of API design, deployment, performance optimization, version control (e.g., Git), containerization (e.g., Docker), and cloud platforms (e.g., AWS, GCP, Azure) is expected. Preferred qualifications include experience with LangChain, Haystack, or similar LLM orchestration frameworks. Understanding NLP evaluation metrics, prompt engineering best practices, knowledge graphs, semantic search, and document parsing pipelines will be beneficial. Experience deploying models in production, monitoring system performance, and contributing to open-source AI/ML projects are considered advantageous for this role.,

You are an experienced professional with over 10 years of total experience, seeking a new opportunity to showcase your expertise in Python, LLM integration, and GenAI development workflows. Your strong knowledge in prompt engineering, vector databases, retrieval-augmented generation (RAG), and toolchains sets you apart. You have hands-on experience with Agentic AI and Open AI, as well as agent frameworks like LangChain Agents, Semantic Kernel, Haystack, or custom-built agents. Your proven track record includes leading LLM/GenAI projects from Proof-of-Concept to Production, showcasing your deep understanding of modern data workflows including ingestion, transformation, cataloguing, validation, and analytics. Collaboration is key for you, as you have the ability to work across engineering, product, and governance teams. Experience with enterprise data products, MLOps, or DataOps platforms, as well as familiarity with governance workflows and metadata-driven automation, are part of your skill set. Your responsibilities will include understanding clients" business use cases and technical requirements to create elegant technical designs, mapping decisions with requirements, identifying the best solutions, and defining guidelines and benchmarks for NFR considerations during project implementation. You will be responsible for writing and reviewing design documents, reviewing architecture and design, ensuring best practices are followed, and developing overall solutions for functional and non-functional requirements. To excel in this role, you should have a Bachelor's or Master's degree in computer science, Information Technology, or a related field. Your excellent communication and collaboration skills will be essential as you resolve issues raised during code/review and carry out POCs to validate suggested designs and technologies. Join us at Nagarro and be part of a dynamic and non-hierarchical work culture where your expertise will be valued and your contributions will make a difference.,

As an AI Manager, you will be responsible for leading the design, development, and deployment of GenAI solutions to support our cutting-edge analytics platforms. Your role will involve mentoring a team of 35 AI engineers, cultivating a culture of collaboration and growth. You will oversee the entire architecture process, from conceptualization and LLM fine-tuning to deploying and monitoring GenAI applications on cloud platforms for financial analytics. Your tasks will include implementing agentic AI design patterns, utilizing frameworks like Autogen, LangGraph, CrewAI, or creating customized agentic architectures. You will integrate advanced GenAI frameworks, leveraging technologies such as Model Context Protocols (MCP) and Agent-to-Agent (A2A) for complex analytic workflows. Ensuring seamless integration with various databases like vector databases, NoSQL, and SQL for efficient data ingestion and retrieval will be crucial. Collaboration with product leaders, data scientists, and engineering teams is essential to deliver user-centric and enterprise-grade AI features. You will be a proponent of best practices in pipeline automation, model evaluation, ethical AI usage, and continuous system enhancement. Additionally, your engagement in open-source contributions on platforms like GitHub or Kaggle will be highly appreciated. In terms of qualifications, you should hold a bachelor's or master's degree in computer science, statistics, mathematics, engineering, or a related field. With 9 to 12 years of experience in machine learning and computer vision, emphasizing large language models, you should be proficient in Python and its data science libraries like pandas, numpy, TensorFlow, pytorch, HuggingFace, LangChain, or Haystack. Demonstrating sound coding principles and familiarity with RAG practices and SLM fine-tuning are required skills. Experience in deploying and managing data science solutions on cloud services such as Azure, AWS, or GCP is essential. Proficiency in sourcing data from SQL and NoSQL databases is necessary, along with basic database knowledge. Possessing a Kaggle profile that showcases your expertise will be advantageous. Strong communication and presentation skills are mandatory, as well as the ability to balance independent and collaborative work in a fast-paced environment. Ideally, your educational background should include a bachelor's or master's degree from premier Indian institutes like IITs, IISc, NITs, BITS, IIITs, etc., in disciplines such as Computer Science, any Engineering field, Mathematics, or related quantitative areas.,

At NiCE, we challenge our limits and strive to be game changers in everything we do. If you are ambitious, innovative, and always play to win, we have the ultimate career opportunity that will ignite your passion for excellence. We are currently looking for an experienced AI Architect who possesses not only strategic thinking skills but also a hands-on approach to coding. In this role, you will be involved in both proof-of-concept (POC) and production-grade AI projects. Your responsibilities will include mentoring team members, establishing ethical AI practices, and making critical decisions regarding AI deployment strategies. It is essential to have a strong background in deploying AI solutions on cloud platforms like Azure or AWS, as well as expertise in building secure and compliant data and machine learning pipelines. As a proactive leader, you will be responsible for bridging the gap between innovation and execution while ensuring scalability, security, and governance in AI systems. Your impact will be significant as you: - Build scalable AI systems and infrastructure capable of handling large datasets, ensuring performance, reliability, and maintainability. - Lead the development of secure and compliant data and machine learning pipelines, aligning with data governance and regulatory standards. - Design, develop, and implement AI models and algorithms to solve real-world business problems. - Mentor team members on AI technologies, best practices, and system architecture. - Collaborate with stakeholders to identify AI-driven innovation opportunities and translate business requirements into technical solutions. - Promote ethical and responsible AI practices across the organization. - Take ownership of strategic decisions related to AI deployment and lifecycle management. - Conduct research and implement machine learning algorithms, including Retrieval-Augmented Generation (RAG) techniques. - Develop AI applications using modern frameworks and run experiments to enhance model performance. - Define and implement AI project Software Development Lifecycle (SDLC) processes. To be successful in this role, you should have: - Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field. - Proven experience as an AI Architect with a track record of deploying AI solutions in production. - Strong expertise in AI/ML technologies, cloud platforms, and secure data management. - Proficiency in programming languages such as Python, .NET, and AI/ML frameworks. - Experience with AI project SDLC, CI/CD for ML, and AI testing strategies. - Familiarity with DevOps and Data Engineering tools and practices. - Strong analytical and problem-solving skills. - Excellent communication skills to convey complex technical concepts. Join NiCE, a global company where innovation and collaboration thrive. Embrace the NICE-FLEX hybrid work model for maximum flexibility and endless opportunities for growth and development. If you are passionate, innovative, and ready to raise the bar, come join us at NiCE! Requisition ID: 7474 Reporting into: Tech Manager Role Type: Individual Contributor About NiCE: NICELtd. (NASDAQ: NICE) is a global leader in software products used by over 25,000 businesses worldwide. With a focus on delivering exceptional customer experiences and ensuring public safety, NiCE is known for its innovation in AI, cloud, and digital domains. Join our team of over 8,500 employees across 30+ countries and be part of our journey towards excellence.,

We are looking for a skilled, motivated, and quick-learning Full Stack Developer to join our team dedicated to cutting-edge Gen AI development work. As a Full Stack Developer, you will be responsible for creating innovative applications and solutions that encompass both frontend and backend technologies. While our solutions often involve the use of Retrieval Augmented Generation (RAG) and Agentic frameworks, your role will extend beyond these technologies to encompass a variety of AI tools and techniques. Your responsibilities will include developing and maintaining web applications using Angular, NDBX frameworks, and other modern technologies. You will design and implement databases in Postgres DB, employ ingestion and retrieval pipelines utilizing pgvector and neo4j, and ensure the implementation of efficient and secure data practices. Additionally, you will work with various generative AI models and frameworks such as LangChain, Haystack, and LlamIndex for tasks like chucking, embeddings, chat completions, and integration with different data sources. You will collaborate with team members to integrate GenAI capabilities into applications, write clean and efficient code adhering to company standards, conduct testing to identify and fix bugs, and utilize collaboration tools like GitHub for effective team working and code management. Staying updated with emerging technologies and applying them to operations will be essential, showcasing a strong desire for continuous learning. Qualifications and Experience: - Bachelor's degree in Computer Science, Information Technology, or a related field with at least 6 years of working experience. - Proven experience as a Full Stack Developer with a focus on designing, developing, and deploying end-to-end applications. - Knowledge of front-end languages and libraries such as HTML/CSS, JavaScript, XML, and jQuery. - Experience with Angular and NDBX frameworks, as well as database technologies like Postgres DB and vector databases. - Proficiency in developing APIs following OpenAPI standards. - Familiarity with generative AI models on cloud platforms like Azure and AWS, including techniques like Retrieval Augmented Generation, Prompt engineering, Agentic RAG, and Model context protocols. - Experience with collaboration tools like GitHub and docker images for packaging applications. At Allianz, we believe in fostering a diverse and inclusive workforce. We are proud to be an equal opportunity employer that values bringing your authentic self to work, regardless of background, appearance, preferences, or beliefs. Together, we can create an environment where everyone feels empowered to explore, grow, and contribute to a better future for our customers and the global community. Join us at Allianz and let's work together to care for tomorrow.,

As an AI Architect at NiCE, you will be responsible for building scalable AI systems and infrastructure capable of handling large datasets while ensuring performance, reliability, and maintainability. You will lead the development of secure, compliant data and machine learning pipelines to align with data governance and regulatory standards such as GDPR. Your role will involve designing, developing, and implementing AI models and algorithms to solve real-world business problems, contributing to both proof-of-concept (POC) and production-grade solutions. Mentoring and guiding team members on AI technologies, best practices, and system architecture will be a key aspect of your role, fostering a culture of continuous learning and innovation within the organization. You will collaborate with cross-functional stakeholders to identify opportunities for AI-driven innovation and translate business requirements into technical solutions. Additionally, you will be responsible for establishing and promoting ethical and responsible AI practices across the organization. Your impact will also include taking ownership of strategic decisions related to AI deployment, architecture, and lifecycle management. You will conduct research and implement appropriate machine learning algorithms, including Retrieval-Augmented Generation (RAG) techniques and integration with Vector Databases. Furthermore, you will develop and maintain AI applications using modern frameworks such as TensorFlow, PyTorch, LangChain, and Haystack, running experiments to evaluate and improve model performance. To excel in this role, you should hold a Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Proven experience as an AI Architect or in a similar senior AI/ML role is required, along with a track record of deploying multiple AI solutions in production. Proficiency in cloud platforms such as Azure or AWS is essential, as well as strong expertise in AI/ML technologies, RAG architectures, and Vector Databases. Your proficiency in programming languages like Python, .NET, or similar, along with familiarity with AI/ML frameworks and libraries, will be crucial. Experience with AI project Software Development Lifecycle (SDLC), model versioning, CI/CD for ML, and AI testing strategies is also necessary. Strong analytical and problem-solving skills, along with excellent communication skills to convey complex technical concepts, are highly valued in this position. Join NiCE, a global company known for market disruption and innovation, where you will work in a fast-paced, collaborative, and creative environment. Embrace the NICE-FLEX hybrid model that offers maximum flexibility with a balance of office and remote work, enabling teamwork, collaboration, and innovation. If you are passionate, innovative, and eager to push boundaries, NiCE offers endless internal career opportunities for growth and development across various roles, disciplines, domains, and locations.,

We will count on you to: Identify opportunities which add value to the business and make the process more efficient. Invest in understand the core business including products, process, documents, and data points with the objective of identifying efficiency and value addition opportunities. Design and develop end-to-end NLP/LLM solutions for document parsing, information extraction, and summarization from PDFs and scanned text. Develop AI applications to automate manual and repetitive tasks using generative AI and machine learning. Fine-tune open-source LLMs (like LLaMA, Mistral, Falcon, or similar) or build custom pipelines using APIs (OpenAI, Anthropic, Azure OpenAI). Build custom extraction logic using tools like LangChain, Haystack, Hugging Face Transformers, and OCR libraries like Tesseract or Azure Form Recognizer. Create pipelines to convert outputs into formatted Microsoft Word or PDF files using libraries like docx, PDFKit, ReportLab, or LaTeX. Collaborate with data engineers and software developers to integrate AI models into production workflows. Ensure model performance, accuracy, scalability, and cost-efficiency across business use cases. Stay updated with the latest advancements in generative AI, LLMs, and NLP research to identify innovative solutions. Design, develop, and maintain robust data pipelines for extracting, transforming, and loading (ETL) data from diverse sources. As the operational scales updesign and implement scalable data storage solutions and integrate them with existing systems. Utilize cloud platforms (AWS, Azure, Google Cloud) for data storage and processing. Conduct code reviews and provide mentorship to junior developers. Stay up-to-date with the latest technology trends and best practices in data engineering and cloud services. Ability to lead initiatives and deliver results by engaging with cross-functional teams and resolving data ambiguity issues. Be responsible for the professional development of your projects and institute a succession plan. What you need to have: Bachelors degree in Engineering, Analytics, or a related field, MBA, Computer Applications, IT, Business Analytics, or any discipline. Proven experience of 8-12 years in Python development Hands-on experience with frameworks and libraries like Transformers, LangChain, PyTorch/TensorFlow, spaCy, Hugging Face, and Haystack. Strong expertise in document parsing, OCR (Tesseract, AWS Textract, Azure Form Recognizer), and entity extraction. Proficiency in Python and familiarity with cloud-based environments (Azure, AWS, GCP). Experience deploying models as APIs/microservices using FastAPI, Flask, or similar. Familiarity with PDF parsing libraries (PDFMiner, PyMuPDF, Apache PDFBox) and Word generation libraries (python-docx, PDFKit). Solid understanding of prompt engineering and prompt-tuning techniques. Proven experience with data automation and building data pipelines. Proven track record in building and maintaining data pipelines and ETL processes. Strong knowledge of Python libraries such as Pandas, NumPy, and PySpark, Camelot. Familiarity with database management systems (SQL and NoSQL databases). Experience in designing and implementing system architecture. Ability to operate in a multi layered technology architecture and shape the technology maturity of the organization. Solid understanding of software development best practices, including version control (Git), code reviews, and testing frameworks (PyTest, UnitTest). Strong attention to detail and ability to work with complex data sets. Effective communication skills to present findings and insights to both technical and non-technical stakeholders. Specify superior listening, verbal and written communication skills Excellent project management and organization skills Superlative stakeholder management skills - ability to positively influence stakeholders. Synthesis skills- Ability to connect the dots and answer the business question. Excellent problem-solving, structuring and critical-thinking skills. Ability to work independently and collaboratively in a fast-paced environment.

• Bachelor's degree in Computer Science, Information Technology, or related field • At least 4+ years of relevant experience in full stack development. • Interest and experience in working with GenAI solution implementations. • Hands-on experience with front-end technologies such as HTML, CSS, JavaScript, and frameworks like React or Angular. • Experience with back-end technologies such as Node.js, Python, or Java. • Familiarity with database management systems like MySQL, PostgreSQL, or MongoDB. • Hands-on experience preferred in cloud platforms (AWS/Azure). • Fair knowledge in containerisation (docker) and their orchestration platforms like Kubernetes • Proficiency in version control systems like Git. • Strong problem-solving and analytical skills. • Good understanding of Agile software development frameworks and tools like JIRA. • Open-minded, good communication and interpersonal skills. Preferred/Additional Technical And Professional Expertise • Has good understanding of traditional enterprise technology stack and enterprise networking concepts • Use different generative AI models & frameworks such as LangChain, Haystack, LlamIndex etc for chucking, embeddings, chat completions, integration with different data sources etc. • Experience working with generative foundational AI models and using API endpoints from Azure/AWS to build applications on top of these foundational models for RAG, fine-tuning approaches.

Required Skills & Experience: 4+ years of experience in penetration testing, red teaming or offensive security. 1+ years working with AI/ML or LLM-based systems. Deep familiarity with LLM architectures (e.g., GPT, Claude, Mistral, LLaMA) and pipelines (e.g., LangChain, Haystack, RAG-as-a-Service). Strong understanding of embedding models, vector databases (Pinecone, Weaviate, FAISS), and API-based model deployments. Experience with adversarial ML, secure inference, and data integrity in training pipelines. Experience with red team infrastructure and tooling such as Cobalt Strike, Mythic, Sliver, Covenant, and custom payload development. Proficient in scripting languages such as Python, PowerShell, Bash or Go.

*****GenAI DevOps Engineer AWS Bedrock***** *****Pune Hinjewadi***** *****Immediate Joiners Preferred***** *****Minimum 4 Days WFO***** Job Description: We are seeking a highly experienced GenAI DevOps Engineer to join our dynamic team in Pune. The ideal candidate will have a strong background in building, deploying, and optimizing Generative AI applications on AWS Bedrock, along with expertise in DevOps practices. You will be responsible for automating infrastructure, managing CI/CD pipelines, and ensuring high performance and reliability of AI models. Key Responsibilities: Design, develop, and deploy Generative AI applications leveraging AWS Bedrock and SageMaker. Automate infrastructure provisioning and deployment processes. Build and maintain robust CI/CD pipelines using CodePipeline and CodeBuild. Monitor application and model performance using CloudWatch, Prometheus, and Grafana. Optimize AI models for performance, scalability, and cost-efficiency. Work with RAG (Retrieval-Augmented Generation) tools such as LangChain, Haystack, and LlamaIndex for building advanced AI solutions. Collaborate with data scientists and developers to streamline model deployment and monitoring. Required Skills: Extensive hands-on experience with AWS Bedrock and SageMaker. Strong expertise in CI/CD tools: CodePipeline, CodeBuild. Proficiency with monitoring tools: CloudWatch, Prometheus, Grafana. Experience with RAG frameworks like LangChain, Haystack, and LlamaIndex. Solid understanding of DevOps best practices and automation. Ability to troubleshoot and optimize AI deployment pipelines. Excellent problem-solving and communication skills. Preferred Skills: Knowledge of containerization (Docker, Kubernetes). Familiarity with scripting languages (Python, Bash). Experience with cloud security best practices. Understanding of machine learning lifecycle management. Mandatory Skills: AWS Bedrock and SageMaker expertise. CI/CD pipeline automation. Monitoring and performance optimization. RAG-based application development.

Job Title: Generative AI Specialist Experience: Total 7+ Years | Relevant - 3 to 5 Years Location: Hyderabad Employment Type: Full-Time Job Description We are seeking a highly skilled and innovative Generative AI Engineer to join our team. The ideal candidate will have a strong background in designing, developing, and deploying AI models, particularly in the domain of generative AI and large language models (LLMs). Key Responsibilities Design & Development: Architect and build generative AI models, algorithms, and frameworks. Model Implementation: Integrate AI models into existing systems and applications. LLM Expertise: Work with tools like LangChain, Haystack, and apply prompt engineering techniques. Data Handling: Preprocess and analyze data for model training and evaluation. Cross-functional Collaboration: Partner with data scientists, product managers, and other stakeholders. Testing & Deployment: Evaluate model performance and deploy models to production. Monitoring & Optimization: Track model performance and continuously improve results. Research & Innovation: Stay updated with the latest advancements in generative AI. Required Skills Proficiency in Python for AI development. Strong understanding of Generative AI , NLP , and LLMs . Experience with RAG pipelines and vector databases . Familiarity with frameworks like LangChain , Haystack , and other open-source libraries. Knowledge of prompt engineering and tokenization . Experience in fine-tuning and integrating AI models in production. Excellent communication and problem-solving skills. Optional Skills Experience with cloud platforms (GCP, AWS, Azure). Familiarity with MLOps and DevOps practices. Why Join Us? Work on cutting-edge AI technologies. Collaborate with a passionate and talented team. Opportunity to innovate and shape the future of AI applications. How to Apply Interested candidates can apply directly through Naukri or send your updated resume to shilpa.shapur@Excelra.com

Description: Job Description: We are looking for an experienced Python Developer with expertise in AI/ML to join our team. The ideal candidate should have strong Python development skills and hands-on experience with AI/ML frameworks, LangChain, Haystack, and LangGraph . Key Responsibilities: Develop and optimize AI/ML-driven applications using Python. Implement and enhance solutions leveraging LangChain, Haystack, and LangGraph . Collaborate with cross-functional teams to integrate AI/ML models into production systems. Design and develop scalable machine learning pipelines and APIs. Debug, optimize, and maintain AI-based applications. Requirements: 310 years of experience in Python development , with a focus on AI/ML. Strong expertise in LangChain, Haystack, and LangGraph . Experience in developing and deploying ML models in a production environment. Familiarity with NLP, deep learning, and vector databases is a plus. Excellent problem-solving skills and ability to work independently or in a team.

Hiring AI & Data Retrieval Engineer with expertise in NLQ, Text-to-SQL, LLMs, LangChain, pgVector, PostgreSQL, vector search, Python, AI libraries, Agentic AI & API integration. Exp with NLP, RAG, BI tools, live projects & LLM fine-tuning preferred.