Senior Software Engineer - AI Governance

Jsr-Tech-Consulting; United States; Remoto; USD 140.000 - 190.000; Tempo pieno

Vantaggi offerti da questo lavoro

Remote work flexibility

Descrizione del lavoro

Jsr-Tech-Consulting is seeking a Senior Software Engineer to design, develop, and maintain scalable governance software for a major financial client. You will work on AI governance, inventory, automation, and platform integrations with cloud-native patterns on AWS.

Responsibilities include building APIs, microservices, and workflows, plus collaborating with Product Owners, Risk, Compliance, and Responsible AI teams to deliver secure, automated governance solutions for enterprise AI adoption.

Competenze

• 5+ years of software engineering experience.
• Experience building enterprise apps and integrations.
• Experience in Agile delivery and cloud-based solutions.
• Hands-on AWS development experience.

Mansioni

• Design, develop, and maintain scalable software solutions for governance.
• Build reusable services, APIs, microservices, and integrations.
• Develop cloud-based solutions using AWS and modern architectures.
• Lead technical discussions and ensure secure coding practices.

Conoscenze

React

Python

SQL

AWS

CI/CD

Distributed systems

Agile delivery

Formazione

Bachelor's degree in Computer Science / Software Engineering / IT or related field

Strumenti

Node.js

Docker

Git

REST APIs

AWS Lambda

Amazon ECS / EKS

Amazon S3

API Gateway

CloudWatch

Descrizione del lavoro

Remote right to hire position with a major financial firm. Must have skills - React, Python, SQL, AWS, CI/CD

The Senior Software Engineer is responsible for designing, developing, and maintaining scalable technology solutions that support AI governance ecosystem. This role will focus on the evolution of the AI Product Inventory, workflow automation, control validation, platform integrations, cloud-native capabilities, and data management.

The engineer will work closely with Product Owners, Data Engineers, Platform Engineers, Risk, Compliance, and Responsible AI stakeholders to deliver secure, scalable, and highly automated governance solutions that support enterprise AI adoption. This role combines hands‑on software development with technical leadership and solution design responsibilities.

Key Responsibilities

Platform Development & Engineering

• Design, develop, and maintain scalable software solutions supporting Responsible AI governance processes.
• Build and enhance capabilities within the Responsible AI platform and related governance platforms.
• Develop reusable services, APIs, microservices, and integration frameworks.
• Design secure, performant, and resilient applications using modern software engineering practices.
• Develop and deploy cloud‑based solutions using AWS services and cloud-native architecture patterns.

Systems Integration

• Integrate governance platforms with enterprise systems including AWS, CMDB, ServiceNow, Identity and Access Management solutions, data repositories, and reporting platforms.
• Develop RESTful APIs and event‑driven integrations.
• Automate data exchanges and artifact collection across platforms.
• Build AWS‑based integrations using services such as Amazon API Gateway, AWS Lambda, Amazon S3, and event‑driven services where appropriate.

Automation & Workflow Management

• Design and implement workflow automation for AI intake, review, approval, monitoring, and control processes.
• Improve operational efficiency through automation and orchestration.
• Support implementation of governance control gates and evidence collection processes.
• Develop workflow solutions using BPMN/Camunda and Groovy scripting.

Data & Solution Quality

• Implement validation, reconciliation, and quality controls for AI inventory and governance data.
• Develop monitoring and observability solutions, including Amazon CloudWatch or comparable enterprise monitoring capabilities.
• Support reporting, analytics, and dashboard capabilities.

Technical Leadership

• Provide technical guidance to engineers and developers.
• Participate in architecture reviews and technology selection decisions.
• Promote software engineering best practices, secure coding standards, and DevSecOps principles.
• Contribute to technical roadmaps and platform strategy.

Collaboration & Governance

• Partner with Product Owners and business stakeholders to define requirements.
• Collaborate with Responsible AI, Risk, Compliance, Legal, and Technology teams.
• Produce and maintain technical documentation, architecture diagrams, operational runbooks, and support materials.

Required Qualifications

Education

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field.
• Equivalent practical experience may be considered.

Experience

• 5+ years of software engineering experience.
• Experience developing enterprise applications and integrations.
• Experience working in Agile delivery environments.
• Experience supporting cloud‑based solutions and distributed systems.
• Hands‑on experience developing, deploying, or supporting applications within AWS environments.

Technical Skills

Programming Languages

• Python
• JavaScript / TypeScript

Frameworks & Development

• Node.js
• React
• Microservices architecture

APIs & Integration

• REST APIs
• OAuth/OIDC
• Enterprise application integration patterns
• Event‑driven architectures

Cloud & AWS Technologies

• AWS Lambda for serverless application development
• Amazon ECS / EKS for containerized workloads
• Amazon S3 for object storage
• Amazon API Gateway for API management and integration
• AWS Identity and Access Management (IAM) for roles and access management
• Amazon CloudWatch for application monitoring, logging, and observability
• AWS Secrets Manager for secrets and credential management
• Amazon RDS and/or DynamoDB for application data persistence
• Docker
• CI/CD pipelines
• Git-based source control

Data Technologies

• SQL databases
• Data validation and reconciliation

Workflow & Process Automation

• BPMN / Camunda workflow orchestration
• Groovy scripting within workflows
• Control gates and evidence collection

Software Engineering Practices

• SDLC
• DevSecOps
• CI/CD
• Secure coding standards
• System design and architecture

Preferred Experience

• Responsible AI governance platforms
• AI/ML lifecycle management solutions
• ModelOp Center administration and configuration
• Regulatory, risk, compliance, or governance workflows
• Enterprise workflow automation
• Model inventory and model risk management processes
• Amazon Bedrock or other AWS AI/ML services
• Building or integrating Generative AI applications within AWS
• AWS cloud architecture and deployment patterns

Core Professional Skills

• Strong problem-solving capability.
• Excellent communication skills.
• Ability to translate business requirements into technical solutions.
• Ability to lead technical discussions and influence architecture decisions.
• Strong collaboration across technical and business teams.
• Continuous learning mindset.
• Ability to operate effectively in highly regulated environments.

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