About The Position

Blake Willson Group is seeking a Senior Cloud, Data & AI Engineer to lead the architecture, development, and delivery of innovative cloud, data, process intelligence, and AI solutions. This role will own technical delivery across AWS GovCloud and Celonis environments, with a focus on building secure, scalable, and reusable solutions for federal clients. The ideal candidate brings deep software and data engineering expertise, hands-on AWS experience, and practical experience with Celonis and AI/agentic technologies.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Information Technology, Business, or a related field.
  • 7+ years of professional software or data platform engineering experience, with a proven track record of building and operating production systems at scale.
  • 5+ years of experience with Python and SQL, including deep hands-on AWS experience across serverless compute, managed data stores, messaging, IAM, encryption, and infrastructure as code using Terraform, CDK, or CloudFormation.
  • 5+ years of experience with cloud-native data and AI solutions, including hands-on Celonis experience with process mining, data models, Knowledge Models, and PQL, as well as experience building or integrating LLM-based or agentic systems.
  • Must be currently authorized to work in the United States on a full-time basis and have the ability to obtain a Public Trust Clearance.

Nice To Haves

  • Prior engineering experience with Celonis, AWS, or a Celonis implementation partner.
  • AWS Certified Solutions Architect and/or Celonis certifications such as Data Engineer, Process Intelligence Developer, or Automation.
  • Experience with AWS GovCloud, FedRAMP, NIST 800-53, and Authority to Operate processes for cloud-hosted analytics and AI systems.
  • Experience with object-centric process mining, Celonis ML Workbench, Blueprint API, and Marketplace packaging.
  • Federal financial management domain knowledge, including OMB Circular A-123, internal controls, PIIA, improper payments, grants management, or financial close and reporting.
  • Experience with Azure data and AI services, OneStream, Workiva, or Power BI.
  • Experience with Agile delivery methodologies, including Scrum or Kanban, and strong communication skills with executive and technical audiences.

Responsibilities

  • Architect, implement, and operate cloud-native services on AWS, including API Gateway, Lambda, Fargate, DynamoDB, SQS, S3, KMS, IAM, and CloudWatch, using infrastructure as code, CI/CD, observability, security, and tenancy controls.
  • Build data ingestion, transformation, and API components for large-scale, multi-source data platforms, including ETL and streaming pipelines, authentication and authorization, and data quality validation.
  • Develop and extend Celonis solutions, including Data Connections, Data Integration transformations, object-centric data models, event logs, Knowledge Models, PQL metrics, Studio Views, and Action Flows.
  • Design and build agentic AI workflows using managed LLM services such as Amazon Bedrock and Azure OpenAI, as well as Celonis AI capabilities, with appropriate evaluations, guardrails, and traceability.
  • Own system architecture and technical direction for Innovation Lab products, including design decisions, code reviews, engineering standards, testing, security, and observability.
  • Lead end-to-end technical delivery of the A-123 Continuous Controls Monitoring solution and additional Innovation Lab products from prototype through pilot and production deployment.
  • Package solutions for reuse across federal agencies through parameterized configuration, automated deployment, versioning, and reference architectures.
  • Support capability demonstrations and post-award implementation activities, including source system mapping, environment configuration, and deployment into agency and FedRAMP-authorized cloud environments.
  • Collaborate with Celonis and AWS partner engineering teams on solution certification, marketplace listings, and partner program requirements.
  • Establish scalable engineering practices that improve reliability, data accuracy, deployment efficiency, and the ability to rapidly stand up solutions for new agency environments.
  • Maintain a focus on measurable business impact, including reducing manual control testing, audit, and review hours and increasing the use of Innovation Lab solutions across client engagements, demonstrations, and proposals.
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