Principal Software Engineer

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
Legacy Product Modernization

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
Cross-Functional Leadership

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
Orchestration Platform Ownership

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
Enterprise AI Infrastructure

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
Innovation & Research

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

Qualifications

Technical Expertise

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
AI/ML Systems
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
Enterprise Architecture
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)
Platform Engineering
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