Principal Software Engineer

Overview

As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference.

At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com

Business Summary

The Deltek Engineering and Technology team builds best-in-class solutions to delight customers and meet their business needs. We are laser-focused on software design, development, innovation and quality. Our team of experts has the talent, skills and values to deliver products and services that are easy to use, reliable, sustainable and competitive. If you're looking for a safe environment where ideas are welcome, growth is supported and questions are encouraged – consider joining us as we explore the limitless opportunities of the software industry.

Position Responsibilities

AI Platform Architecture & Strategy

• Lead architectural design for next-generation AI platform enabling agentic capabilities across Deltek's product portfolio
• Define technical strategy for integrating domain agents with existing enterprise systems
• Design multi-agent orchestration architecture using LangGraph, semantic routing, and GraphRAG patterns
• Architect scalable vector database infrastructure for enterprise knowledge management
• Establish platform patterns for agent-to-agent communication and workflow coordination
  
  
  

• Design integration patterns for embedding AI capabilities into existing product suite
• Build abstraction layers that enable legacy systems to consume agentic services
• Define API contracts and event schemas for cross-product AI orchestration
• Create backward-compatible migration paths for legacy codebases
• Architect hybrid architectures balancing legacy constraints with modern AI capabilities
  
  
  

• Partner with ML/AI teams on model deployment, fine-tuning, and prompt engineering strategies
• Collaborate with data science teams on feature engineering and training data pipelines
• Guide technical decisions across engineering, ML, and product teams
• Drive architectural review processes and technical RFC approvals
  
  
  

• Maintain and evolve existing orchestration coding platform architecture
• Optimize multi-phase orchestration engines for performance and reliability
• Design state management strategies for complex, long-running agent workflows
• Implement semantic routing to reduce orchestration latency (current: 7-8s baseline)
• Build observability frameworks for debugging multi-agent interactions
  
  
  

• Design multi-tenant architecture with tenant isolation and resource governance
• Build production MLOps pipelines for model versioning, A/B testing, and rollback
• Architect cost optimization strategies for LLM API usage and GPU workloads
• Define SLAs and design for high availability in mission-critical AI services
  
  
  

• Evaluate emerging AI technologies (autonomous agents, function calling, tool use patterns)
• Prototype advanced capabilities (GraphRAG, multi-modal processing, agent memory systems)
• Drive technical spikes for complex problems (e.g., context window management, agent hallucination mitigation)
• Establish best practices for prompt engineering and chain-of-thought reasoning
  
  
  

• 10+ years of software engineering experience with 3+ years in AI/ML production systems
• Expert Python proficiency: FastAPI, asyncio patterns, LangChain, LangGraph, PyTorch/TensorFlow
• Strong TypeScript/React experience: React 18+, modern hooks, state management, real-time WebSocket integration
• LLM Integration expertise: OpenAI API, Anthropic Claude API, Azure OpenAI, streaming responses
• Vector database architecture: production deployment and optimization
• Multi-agent orchestration: Production experience building agent coordination systems at scale
• Proven track record in architecting platforms serving 1000+ concurrent users
  
  
  

• Experience deploying and fine-tuning LLMs (GPT-4, Claude Sonnet/Opus, Llama 3, Phi-3)
• RAG architecture expertise: naive RAG, GraphRAG, hybrid search, semantic chunking strategies
• Prompt engineering mastery: few-shot learning, chain-of-thought, structured outputs, tool use
• Agent frameworks: LangGraph, AutoGen, CrewAI, Semantic Kernel - production implementations
• Embedding model optimization (OpenAI, Amazon Titan, sentence-transformers)
• Experience with semantic routing, context caching, and token optimization
  
  
  

• Proven ability in designing integration layers for legacy enterprise software modernization
• ERP/Project Management systems: Deltek, Oracle, SAP, or similar enterprise platforms
• API architecture: REST, GraphQL, gRPC, WebSocket - design for scalability and versioning
• Enterprise auth systems: OAuth2, SAML 2.0, SSO (Okta, Azure AD), JWT token management
• Data governance: SOC2, GDPR, HIPAA compliance, audit logging, data residency
• Database design for multi-tenant SaaS (PostgreSQL, MySQL, Redis)
  
  
  

• Backend frameworks: FastAPI, Flask, Django - production deployment and scaling
• Frontend development: React, TypeScript, WebSocket clients, real-time UI patterns
• Containerization: Docker, Kubernetes, Helm charts, container orchestration at scale
• Cloud platforms: AWS (SageMaker, ECS, Lambda, S3) or Azure (ML, AKS, Functions) or Oracle OCI
• Observability: Prometheus, Grafana, OpenTelemetry, distributed tracing, log aggregation
• Event-driven architecture: RabbitMQ, Kafka, Redis Streams - message queue design patterns
• Infrastructure-as-Code: Terraform, CloudFormation, Pulumi - reproducible deployments
• CI/CD pipelines: GitHub Actions, GitLab CI, Jenkins - automated testing and deployment
  
  
  

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Travel Requirements

No

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