We have urgent opening with R systems Bangalore. Exp Leve: 6-8 Yrs Mandatory :Only Immediate joiner Mandatory looking for Bangalore location Candidates only Interested candidates share updated resume at [email protected] Responsibilities
• Build agents on AWS: design, deploy, and operate AI agents on Amazon Bedrock AgentCore, using AgentCore Runtime for hosting, Gateway to expose APIs and Lambda functions as tools (including MCP), Memory for short
- and long-term context, Identity for secure agent access, and Observability for tracing and debugging.
• Build RAG and agent solutions with Amazon Bedrock: implement foundation-model integrations, Knowledge Bases, Agents, and Guardrails, and manage prompts and model selection for cost, latency, and quality.
• Build on Oracle AI Data Platform (AIDP): develop in the AIDP Workbench using Master Catalog assets, Spark notebooks, and workflows; apply medallion (bronze, silver, gold) data patterns; and build knowledge bases and agent flows on governed enterprise data.
• Build on Oracle AI Database: implement AI Vector Search, hybrid (vector + relational) retrieval, Select AI natural-language-to-SQL interfaces, and in-database ML, with embedding pipelines and PL/SQL where needed.
• Integrate across platforms: connect Oracle data services with AWS-hosted AI applications through secure, well-defined APIs and swappable service interfaces.
• Engineer retrieval quality: own chunking and embedding strategy, metadata filtering, reranking, and retrieval tuning, and measure results with repeatable evaluations.
• Secure and govern AI: apply IAM least privilege, database-enforced access control (such as role-based access and data redaction), PII handling, and guardrails that screen for prompt injection and unsafe output. Keep audit trails of agent actions and outcomes.




• Test and evaluate: build evaluation and regression suites for LLM output, track hallucination and accuracy, and verify behavior end to end against real services, not only with unit tests.
• Deploy and operate: ship Python services (for example FastAPI) to production on AWS using Lambda, API Gateway, S3, ECS/EKS, Step Functions, and Secrets Manager. Monitor latency, quality, and cost with CloudWatch and AgentCore Observability.
• Collaborate and document: take part in sprint ceremonies and code and design reviews, and maintain documentation, runbooks, and knowledge-transfer material. Experience & Education
• 6-8 years of software, data, or AI/ML engineering experience, with hands-on delivery of generative AI or LLM-based applications in production or near-production.
• Bachelor’s degree or higher in Computer Science, AI, or a related field is preferred.
• Proven experience building RAG pipelines and agentic workflows, including tool calling and multi-step orchestration.
• Experience with Amazon Bedrock and AWS-native deployment. Hands-on AgentCore experience is strongly preferred.
• Experience with Oracle Database or Oracle AI Database. Experience with the Oracle AI Data Platform is strongly preferred.
• Strong debugging and root-cause analysis skills, including tracing non-deterministic model behavior.
• Clear written and verbal communication, and the ability to work independently in a distributed team.



Technical Skills & Competencies
• Generative AI on AWS: Amazon Bedrock foundation models, Knowledge Bases, Agents, Guardrails, prompt engineering, and model evaluation; Amazon Bedrock AgentCore (Runtime, Gateway, Memory, Identity, Observability, and built-in tools such as Code Interpreter).
• Oracle data and AI: Oracle AI Database (AI Vector Search, Select AI, in-database ML, PL/SQL) and Oracle AI Data Platform (Master Catalog, notebooks, workflows, knowledge bases, agent flows, OCI Generative AI integration).
• AI application engineering: RAG pipelines, agentic workflows, LangChain, LangGraph, or LlamaIndex, Model Context Protocol (MCP), embedding strategy, chunking, reranking, and structured LLM output.
• AWS cloud: Lambda, API Gateway, S3, ECS/EKS, Step Functions, IAM, VPC, CloudWatch, and Secrets Manager.
• Programming: Python (primary), REST APIs, and SQL; FastAPI or similar async frameworks.
• Security and governance: IAM least privilege, data privacy controls, PII handling, and responsible-AI guardrails.
• Delivery: Agile/Scrum, Git and CI/CD, Docker, Jira and Confluence, and explicit documentation. Preferred (Nice to Have)
• Experience with AgentCore Identity and Gateway for secure, tool-enabled agents.
• Experience with Oracle Cloud Infrastructure (OCI), Apache Spark, or medallion-architecture data pipelines.
• Infrastructure as code (for example Terraform) and Kubernetes experience.
• Experience with agent frameworks such as Strands Agents, or with migrating Bedrock Agents to a code-first framework.
• Experience with LLM gateways, token and cost tracking, and usage analytics.
• Relevant certifications, such as AWS or Oracle Cloud Infrastructure Generative AI certifications.

📌 Urgent opening with R systems- Bangalore- agent engineering on AWS (India)
🏢 R Systems
📍 India