15 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design, build, and deploy A2A communication architectures and multi-agent workflows for autonomous collaboration, delegation, and multi-step business processes.
- Integrate proprietary and open-source LLMs with enterprise APIs, tool-calling methods, and third-party SaaS applications.
- Implement RAG, enterprise grounding, vector search, and hybrid search strategies for reliable inter-agent operations.
- Provision and manage AWS, Azure, and GCP environments using Terraform for high-concurrency LLM inference and agent coordination.
- Create CI/CD pipelines and support testing, deployment, versioning, LLM evaluation, and agentic workflow lifecycle management.
- Apply security and network controls including VPCs, secure API gateways, encryption, IAM, and protected inter-agent communication.
- Build observability and evaluation systems to monitor agent interactions, accuracy, token spending, model drift, and agent loops.
- Document LLM integration protocols, A2A interaction flows, and cloud infrastructure deployments.
Requirements
- Deep experience integrating, fine-tuning, and optimizing foundation models, including prompt engineering, tool calling, and structured outputs.
- Proven experience building multi-agent systems, inter-agent messaging pipelines, state management frameworks, and task delegation protocols.
- Hands-on experience with LangGraph, LangChain, AutoGen, LangSmith, or comparable agentic and tracing platforms.
- Strong understanding of AI interoperability standards including MCP and open multi-agent communication specifications.
- Advanced proficiency in Python or TypeScript for backend orchestration, agent memory systems, and API service development.
- Practical knowledge of RAG, vector databases, hybrid search architectures, and context management.
- Hands-on experience with DevOps and infrastructure automation using Terraform, Docker, and Kubernetes.
- Strong knowledge of secure cloud architecture, zero-trust networking, private endpoints, OAuth, SAML, and IAM.
- Experience with logging, distributed tracing, metrics, and evaluation of non-deterministic multi-agent workflows.
- Knowledge of enterprise agentic and workflow platforms such as Workday A2A, Salesforce Agentforce, and ServiceNow AI Agents.
Benefits
- Distributed-company work model with flexible locations and schedules for many roles.
- Health coverage for employees and families in many locations.
- Generous vacation allowance.
- Up to $2,000 matching for financial donations and up to 40 volunteer hours annually.
- At least 16 weeks of parental leave.
- Inclusive culture and equal employment opportunity.
Categories
About Elastic
Elastic builds the Elasticsearch-based platform for enterprise search, observability (logging, metrics, APM), and security (SIEM/endpoint). It sells subscriptions and Elastic Cloud managed services with usage-based pricing, combining open source and proprietary features through Elasticsearch and Kibana. Founded in 2012 and headquartered in San Francisco, Elastic is publicly traded on the NYSE and is used by more than half of the Fortune 500.