Position Overview


We are seeking a rare, highly skilled
hybrid AWS Solutions Architect & Software Developer to join our core
product engineering team. In this role, you will bridge the gap between
high -level cloud architecture and hands -on backend development. You will be
responsible for designing, implementing, and code -authoring the robust cloud
infrastructure that powers our data core.

The primary focus of this position is
architecting and developing the high -throughput pipelines that process raw
"fleet exhaust data" (noise) in AWS and funnel actionable summaries
(signals) into our enterprise presentation layer. You will heavily focus on
complex data orchestrations and integrations across AWS, Salesforce Data Cloud,
MuleSoft, and critical third -party fleet compliance ecosystems.

Key Responsibilities

As a hybrid Architect
and Developer, your responsibilities will span architectural design, core
systems programming, and cross -platform ecosystem integration:

Cloud Architecture & Strategy


- Design & Scale: Architect and optimize secure, scalable,
and cost -effective cloud infrastructures capable of ingesting massive,
high -velocity streaming data environments.

- Infrastructure as Code (IaC): Develop and maintain production -ready
CloudFormation or Terraform templates to ensure fully automated,
repeatable environment deployments.

- CI/CD Leadership: Establish and govern standardized CI/CD
pipelines that continuously decrease time -to -production for new backend
features while enforcing rigorous quality and testing gates.

- Security & Trust: Design and implement a robust Cloud
Trust Architecture ensuring compliance with stringent data protection best
practices and role -based access control.


Backend Software Engineering

- Write Robust Backend Code: Write clean, highly performant, and
scalable code (primarily utilizing Python or Node.js) to build core AWS
backend services, APIs,



and microservices.

- Data Processing & AI: Program state -of -the -art serverless
workflows utilizing AWS Lambda, EventBridge, and Amazon Bedrock to compute
derived risk indicators (e.g., speeding minutes per 100 miles, trend slope
tracking).

- Database & Knowledge Lake Management: Optimize structured and
unstructured data persistence strategies across Amazon S3, RDS instances,
and managed Vector Databases.

- Testing & Quality Assurance: Author and run extensive unit and
integration tests for AWS -based applications, lead code reviews, and
aggressively improve core data processing algorithms.


Multi -Platform Ecosystem Integration

- Ecosystem Orchestration: Architect the ingestion paths for
high -velocity telematics and IoT data, isolating massive volume processing
in AWS before translating relevant indicators to executive CRM workflows.

- Telematics & Compliance Integration: Build and maintain direct
API data pipelines integrating heavy enterprise platforms and third -party
systems including:

- Telematics Infrastructure: Deep integration with providers like
Verizon Connect (VZC) to ingest real -time engine diagnostics, GPS, and
harsh event data.

- Regulatory Compliance: Integrations with FMCSA API systems
(including SAFER, SMS, A&I;, and DataQs datasets).

- Risk & Personnel Platforms: Synchronized identity management
pipelines with Motor Vehicle Record (MVR) monitoring and Learning
Management Systems (LMS) such as Samba Safety, Sentix, or related Risk
Cloud environments.





- Salesforce & MuleSoft Collaboration: Partner closely with
application teams to orchestrate end -to -end event -driven flows using
MuleSoft for bidirectional Roster CRUD logic, linking the AWS Knowledge
Lake cleanly with Salesforce Data Cloud and AgentForce.