Job Description
Job Description
Title: AI Engineer Standard III
Location: Washington, DC 20433
Hybrid Onsite: 4 days per week from Day 1, with a full transition to 100% onsite anticipated soon.
Essential Job Functions:
Architect and Implement AI Solutions
Design and build RAG pipelines using Azure AI/Search and vector databases: chunking, embeddings, hybrid/semantic ranking, re-ranking, evaluation, and citation display.
Build enterprise conversational systems (multi-turn, retrieval-grounded) with prompt lifecycle management, guardrails, audit logging, and telemetry.
Support multiple LLMs and modalities: Azure OpenAI, Llama (Meta), Claude, etc.., and task-specific OSS models (vision, speech), with policy-driven model routing for performance, safety, and cost.
Integrate and Operate AI Infrastructure
Implement Model Context Protocol (MCP) servers integrating with project related areas.
Provide tool functions with RBAC scopes, schema versioning, rate limiting, request/response validation, and audit trails.
Deploy Azure AI Agent Service (AGA) patterns for agent registry/broker/governance with agent telemetry and policy enforcement.
Use Azure Batch for large-scale, parallel inferencing/vectorization jobs; leverage AWS EMR for distributed data/feature processing in AI pipelines.
Develop and Manage Data Pipelines
Build ingestion and enrichment for RAG connectors and ETL/ELT: document normalization, PII redaction, metadata enrichment, SLA/SLO monitoring, and lineage.
Operate large-scale vectorization with quality gates and drift monitoring.
Use Azure Data Factory (ADF) and Azure Databricks for orchestrated, scalable data processing; use AWS EMR for Hadoop/Spark workloads supporting AI features.
Build Agentic AI Solutions
Design secure tool-calling and multi-agent orchestration using Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno, and LangChain or others.
Know how to apply agent governance and MCP-based controls across heterogeneous agents and runtimes (register, observe, govern, retire).
Model Evaluation and Optimization
Evaluate and fine-tune open-source and proprietary models; optimize for quality, latency, safety, and cost with A/B and offline eval suites.
Implement CI/CD with automated tests, security scans. Have knowledge on how to secure model workloads.
Software Engineering Emphasis (Core)
CS fundamentals: algorithms, data structures, complexity, distributed systems, networking, concurrency.
SDLC excellence: clean architecture, design patterns, SOLID principles, unit/integration/e2e tests, testing pyramids.
Secure coding & threat modelling for AI apps: input validation, sandboxed tool functions, secrets hygiene, role-based access & least privilege.
Performance engineering: profiling, caching, vector index tuning, latency/throughput optimization, and cost controls (token/embedding/compute).
Collaboration & Delivery: Agile ceremonies, RACI clarity, cross-functional delivery with product/design/data/security.
Knowledge Requirements – Cloud AI Tech Stack (Azure & AWS)
Azure: Azure OpenAI; Azure AI/Search; Azure Machine Learning; Azure Kubernetes Service (AKS); Azure Functions; Azure API Management; Key Vault; Event Hub; App Insights; Log Analytics; Azure Batch; Azure Data Factory (ADF); Azure Databricks.
AWS: Amazon SageMaker; AWS Bedrock; Amazon Kendra; Amazon Comprehend; AWS Lambda; Amazon API Gateway; AWS Secrets Manager; Amazon S3; Amazon CloudWatch; Elastic Kubernetes Service (EKS); Amazon EMR.
Vector DBs & Indexing: Azure AI Search vector storage, Redis, FAISS/HNSW; hybrid search + semantic ranking.
Frameworks: Semantic Kernel, AutoGen, Microsoft Agent Framework, CrewAI, Agno, LangChain.
Local/Edge Inference: running models locally via Docker/Ollama/vLLM/Triton; GPU provisioning; quantization (GGUF) for Llama-family models.
Educational Qualifications and Experience:
Education: Bachelor’s degree in Computer Science, Engineering, Information Technology, Data Science —or equivalent hands-on expertise.
Experience: 6+ years of software engineering experience, with at least 2+ years in applied LLM/GenAI (RAG, agents, eval, safety).
Certification Requirements:
Mandatory:
Microsoft Certified: Azure AI Fundamentals (AI-900)
Microsoft Certified: Azure Data Fundamentals (DP-900)
Responsible AI certifications
AWS Machine Learning Specialty
TensorFlow Developer
Kubernetes CKA/CKAD
SAFe Agile Software Engineering (ASE)
Additional Value (Preferred):
Microsoft Certified: Azure AI Engineer Associate (AI-102)
Microsoft Certified: Azure Data Scientist Associate (DP-100)
Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
Microsoft Certified: Azure Developer Associate (AZ-204)
Required Skills/Abilities:
GenAI architecture mastery: RAG, vector DBs, embeddings, transformer internals, multi-modal pipelines.
Agentic systems: Azure AI Agent Service patterns, MCP servers, registry/broker/governance, secure tool-calling.
Languages: C# and Python (production-grade), .Net, plus TypeScript for service/UI when needed.
Azure & AWS services (see Knowledge Requirements) with hands-on implementation and operations.
Model ops: eval suites, safety tooling, fine-tuning, guardrails, traceability.
Business & delivery: solution architecture, stakeholder alignment, roadmap planning, measurable impact.
Desired Skills/Abilities (not required but a plus):
LangChain, Hugging Face, MLflow; Kubernetes + GPU scheduling; vector search tuning (HNSW/IVF).
Responsible AI: policy mapping, red-team playbooks, incident response for AI.
Hybrid/multi-cloud deployments using Azure Arc and AWS Outposts; CI/CD for AI workloads across Azure DevOps and AWS CodePipeline.
Company DescriptionASTA Corporate Resource Solutions Inc is one of the Fastest Growing IT Companies in Northern America and the DC Metro Area with its headquarters in Ashburn, Virginia. ASTA CRS is an Information Technology Provider delivering superior quality software development, consulting, and staffing solutions to our client partners. We are 21 Years in this Industry.
ASTA CRS services are uniquely positioned to support clients in achieving profound efficiencies and relentlessly delivering results. ASTA CRS is a long-time and trusted resource for its clients and partners.
Asta CRS, Inc. is an Equal Opportunity Employer M/F/V/D. ASTA CRS is proud to state that we are enrolled with the USCIS for the E-Verification Program.
Company Description
ASTA Corporate Resource Solutions Inc is one of the Fastest Growing IT Companies in Northern America and the DC Metro Area with its headquarters in Ashburn, Virginia. ASTA CRS is an Information Technology Provider delivering superior quality software development, consulting, and staffing solutions to our client partners. We are 21 Years in this Industry. \r\n\r\nASTA CRS services are uniquely positioned to support clients in achieving profound efficiencies and relentlessly delivering results. ASTA CRS is a long-time and trusted resource for its clients and partners.\r\n\r\nAsta CRS, Inc. is an Equal Opportunity Employer M/F/V/D. ASTA CRS is proud to state that we are enrolled with the USCIS for the E-Verification Program.