5 Guardrails Jobs

Experience required: 7+ years Core Generative AI & LLM Skills: * 5+ years in Software Engineering, 1+ year in Generative AI. * Strong understanding of LLMs, prompt engineering, and RAG. * Experience with multi-agent system design (planning, delegation, feedback). * Hands-on with LangChain (tools, memory, callbacks) and LangGraph (multi-agent orchestration). * Proficient in using vector DBs (OpenSearch, Pinecone, FAISS, Weaviate). * Skilled in Amazon Bedrock and integrating LLMs like Claude, Titan, Llama. * Strong Python (LangChain, LangGraph, FastAPI, boto3). * Experience building MCP servers/tools. * Designed robust APIs, integrated external tools with agents. * AWS proficiency: Lambda, API Gateway, DynamoDB, S3, Neptune, Bedrock Agents * Knowledge of data privacy, output filtering, audit logging * Familiar with AWS IAM, VPCs, and KMS encryption Desired Skills: * Integration with Confluence, CRMs, knowledge bases, etc. * Observability with Langfuse, OpenTelemetry, Prompt Catalog * Understanding of model alignment & bias mitigation

You are looking for a talented individual to join our team as a Pega Certified Lead System Architect/CSSA in Pune, India. In this role, you will be responsible for designing and implementing enterprise-level solutions using the Pega platform. The ideal candidate should have hands-on expertise in Pega version 7.x or greater, integration using connectors and services, and working in an Agile Scrum environment. Your responsibilities will include leading the design and architecture of Pega applications, collaborating with cross-functional teams to define and implement solutions, creating system architecture diagrams and documentation, and interfacing with clients daily to understand requirements and provide technical guidance. It will be essential to ensure adherence to Pega standards and guardrails throughout the development lifecycle. To qualify for this position, you must be a Pega Certified Senior System Architect (PCSSA) and Certified Pega Lead System Architect with a minimum of 5 years of relevant design and architecture experience. Additionally, you should have at least 4 years of experience with Pega version 7.x or greater, 2 years of experience with Connectors and Services in Pega for external system integration, and 2 years of experience working in Agile Scrum environments. Preferred skills for this role include strong documentation skills, excellent communication and client-facing skills, and a deep understanding of Pega Standards and Guardrails. If you meet these qualifications and are ready to take on this exciting opportunity, we would love to hear from you.,

Experience required: 7+ years Core Generative AI & LLM Skills: * 5+ years in Software Engineering, 1+ year in Generative AI. * Strong understanding of LLMs, prompt engineering, and RAG. * Experience with multi-agent system design (planning, delegation, feedback). * Hands-on with LangChain (tools, memory, callbacks) and LangGraph (multi-agent orchestration). * Proficient in using vector DBs (OpenSearch, Pinecone, FAISS, Weaviate). * Skilled in Amazon Bedrock and integrating LLMs like Claude, Titan, Llama. * Strong Python (LangChain, LangGraph, FastAPI, boto3). * Experience building MCP servers/tools. * Designed robust APIs, integrated external tools with agents. * AWS proficiency: Lambda, API Gateway, DynamoDB, S3, Neptune, Bedrock Agents * Knowledge of data privacy, output filtering, audit logging * Familiar with AWS IAM, VPCs, and KMS encryption Desired Skills: * Integration with Confluence, CRMs, knowledge bases, etc. * Observability with Langfuse, OpenTelemetry, Prompt Catalog * Understanding of model alignment & bias mitigation

Please look below highlighted areas in resume Landing Zones using AWS Control Tower, Service Catalog, and Guardrails . This is must in profiles and its missing in resume. Architect cloud migration strategies, ensuring seamless workload transition to AWS. Implement Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, and AWS CDK. Design and manage AWS Landing Zones using AWS Control Tower, Service Catalog, and Guardrails . Optimize AWS cloud services across IaaS, PaaS, and SaaS models to enhance agility and scalability. Ensure compliance with security best practices, governance frameworks, and AWS Well-Architected principles. Establish multi-account strategies using AWS Organizations, SCPs, and IAM permissions. Provide guidance on cloud automation, serverless computing, and containerization using ECS/EKS/Fargate. Work with cross-functional teams to drive cost efficiency, performance optimization, and cloud governance. Mentor teams to upskill AWS capabilities and develop cloud-native applications.

About the Role The LLM Applications Engineer transforms AI prototypes into modular, secure, and production-ready workflows. This role focuses on orchestrating AI agents, implementing observability, and building toolkits that accelerate internal and external adoption. Key Duties/ Responsibilities • Develop agent orchestration using frameworks like LangChain, CrewAI, AutoGen. • Build reusable APIs, SDKs, and configuration layers for internal consumption. • Implement prompt safety measures and fallback handling using Rebuff, Guardrails AI. • Ensure agent workflows are observable and CI/CD friendly. • Collaborate with platform and backend engineers for deployment enablement. Leadership Skills: • Ownership of agent toolkit delivery. • Cross-functional collaboration with platform and AI scientists. • Documentation and internal adoption support. Required Technical Skills: • Node.js, Python, Docker, REST APIs. • LangChain, Rebuff, LCEL, Guardrails, LangSmith. • CI/CD tooling, OpenTelemetry, workflow orchestration (Airflow, Prefect). • Experience implementing agent safety using Rebuff, Guardrails, or similar tools. • Familiarity with one or more orchestration frameworks: LangChain, CrewAI, AutoGen (or equivalents). Qualification: 5+ years in backend/devops roles, with 2+ years in AI workflow orchestration.