Senior Engineer (Agentic AI Platforms)

DXC Technology • Ashburn, VA

13d • Hybrid

About The Position

DXC Technology (NYSE: DXC) helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private, and hybrid clouds. The world’s largest companies and public sector organizations trust DXC to deploy services across the Enterprise Technology Stack to drive new performance levels, competitiveness, and customer experience. Learn more about how we deliver excellence for our customers and colleagues at DXC.com. Location: Hybrid with up to 50% travel to client location. Candidates located within 25 miles of a DXC office will be required to work onsite 2 times per week. Role Summary: Hands‑on engineer building agentic applications and platform components: planners, tools, episodic + vector memory, RAG services, guardrails, evaluation pipelines, and production APIs. Deliver on Azure/AWS/GCP with a focus on reliability, observability, and speed‑to‑value.

Requirements

• Strong Python (preferred) and one of TypeScript/Node or C#/.NET.
• Practical experience with Azure AI Foundry/Azure OpenAI and one of AWS Bedrock/SageMaker or Google Vertex AI; familiarity with Dataiku.
• Frameworks: Semantic Kernel, LangChain, AutoGen, CrewAI, LangGraph, Prompt flow.
• Vector/RAG: Pinecone, Milvus, Weaviate, pgvector, Cosmos DB Vector, or Elastic; retrieval quality tuning & evals.
• Infra: Containers/K8s (AKS/EKS/GKE), Functions/Lambda/Cloud Run, Terraform/Bicep, GitHub Actions/Azure DevOps.
• Security: OAuth2/OIDC (Entra ID/IAM), secrets (Key Vault/KMS/Secrets Manager), private networking & data minimization.
• Must be legally authorized to work in the United States without requiring sponsorship now or in the future

Nice To Haves

• Databricks (Delta, MLflow) or Microsoft Fabric (Lakehouse) experience or Snowflake.
• Observability stacks (OpenTelemetry, Datadog, Dynatrace, Splunk) and correlation of LLM traces with infra metrics.
• Cloud Tracks – Familiarity with One or More: Azure Track: Azure AI Foundry, Azure OpenAI, Prompt flow, Semantic Kernel, AKS/Functions, Entra ID/Key Vault AWS Track: Bedrock, SageMaker, Guardrails, Kendra, EKS/Lambda, IAM/Secrets Manager GCP Track: Vertex AI, Generative AI Studio, GKE/Cloud Run, BigQuery, Secret Manager

Responsibilities

• Build PoCs/MVPs into hardened services (FastAPI/ASP.NET/Node) on AKS/EKS/GKE or Functions/Lambda/Cloud Run.
• Implement multi‑agent workflows (task routing, planning, HITL), tool adapters (ServiceNow, SAP, Salesforce, Elastic/Splunk, Datadog/Dynatrace), and memory.
• Implement RAG pipelines: ingestion, chunking/windowing, embeddings, hybrid/semantic search, rerankers; integrate vector DBs.
• Instrument telemetry (traces, tokens, cost, latency), define SLIs/SLOs, and create dashboards & alerts.
• Build reusable agent components (planners, tool registries, evaluators), SDKs/CLI, and CI/CD templates (GitHub Actions/Azure DevOps).
• Create evaluation suites (Prompt flow, Langfuse, MLflow/W&B) and guardrail pipelines (toxicity, PII, hallucination checks).
• Author runbooks, deployment guides, and developer docs.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees