DXC Technology-posted 3 months ago
Ashburn, VA
5,001-10,000 employees

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.

  • Client Engagement and Offering Development.
  • 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.
  • 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.
  • Databricks (Delta, MLflow) or Microsoft Fabric (Lakehouse) experience or Snowflake.
  • Observability stacks (OpenTelemetry, Datadog, Dynatrace, Splunk) and correlation of LLM traces with infra metrics.
  • Familiarity with Azure Track: Azure AI Foundry, Azure OpenAI, Prompt flow, Semantic Kernel, AKS/Functions, Entra ID/Key Vault.
  • Familiarity with AWS Track: Bedrock, SageMaker, Guardrails, Kendra, EKS/Lambda, IAM/Secrets Manager.
  • Familiarity with GCP Track: Vertex AI, Generative AI Studio, GKE/Cloud Run, BigQuery, Secret Manager.
  • Flexible work model prioritizing in-person collaboration.
  • Commitment to fostering an inclusive environment.
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