Software Engineer

Title: Software Engineer( Sr. Associate) - Platform Engineering and AI
Duration: 6 months contract +(C2H)
Location: Frisco, TX / NYC, NY/ Chadds Ford, PA / Draper, UT / Wilmington, DE/ Columbus, OH- (hybrid 2 Days/ week onsite)

Job Description
Overview
We are looking for Senior Engineers and Staff Engineers at the Architect level with strong software engineering and platform engineering experience. This is not a traditional Cloud Engineering or Infrastructure/Terraform-focused role.
Strong backend engineering expertise along with frontend development experience and exposure to AI/AI-enabled engineering practices. Candidates should be hands-on engineers with strong programming, architecture, SDK development, automation, and operational efficiency experience.

ONE OF THESE CERTIFICATIONS IS REQUIRED FOR ANY CANDIDATE SUBMITTED (PLEASE OBTAIN A COPY TO PROVIDE):
1. AWS cloud practitioner,
2. Microsoft Azure Fundamentals
3. Google Cloud- Cloud Digital Leader

Minimum Qualifications

• Bachelor’s degree in information technology, Computer Science, Computer Information Systems, Software Engineering, Mathematics, Statistics or related field of study or equivalent, relevant work experience
• 3-5+ years of experience in platform engineering, software engineering, cloud engineering, DevOps, automation engineering, or related disciplines.
• Strong hands-on experience with modern programming languages, cloud-native technologies, automation frameworks, and engineering platforms.
• Proven experience designing and delivering scalable platform solutions, shared services, automation frameworks, reusable components, developer tools, and self-service capabilities.
• Demonstrated experience leading technical initiatives and driving adoption of engineering best practices across teams.

Preferred Qualifications
Relevant industry certifications in cloud platforms, DevOps, platform engineering, software development, automation, AI/ML, data engineering, or related technologies are preferred.

Skills

• Platform Engineering Strategy & Architecture
• Engineering Platforms, Platform Products & Shared Services
• Developer Experience (DevEx) & Self-Service Platforms
• Reusable Components, APIs, SDKs, Frameworks & Accelerators
• Intelligent Automation & AIDLC Enablement
• AI-Assisted Engineering & Agent-Based Development
• Platform Modernization & Cloud-Native Architectures
• Cloud Engineering & Infrastructure as Code (IaC)
• DevOps, CI/CD & Engineering Productivity
• Site Reliability Engineering (SRE) & Operational Excellence
• Monitoring, Observability & Platform Reliability
• Security, Governance & Engineering Controls

The Senior Associate Platform Engineer contributes to the development, configuration, and support of platform services, automation solutions, and cloud-based infrastructure. Assists in building and maintaining automation frameworks, reusable tools, and platform capabilities that improve engineering efficiency, reliability, and software delivery. Supports the implementation of CI/CD workflows, infrastructure automation, and platform observability while adopting modern engineering practices and AI-enabled tools under guidance. Collaborates with engineering, product, and platform teams to deliver scalable solutions, streamline development workflows, and support continuous improvement across the AI-driven development lifecycle.
This role specializes in SDLC automation and intelligent engineering, driving the architecture, standardization, and adoption of reusable frameworks, platform products, components, and self-service capabilities. Engineers leverage modern engineering practices, cloud-native technologies, AI-powered solutions, and agent-based automation to accelerate software delivery, improve platform reliability, enhance developer productivity, and enable intelligent autonomous workflows across the AIDLC.

Essential Job Functions

• Platform Engineering & Platform Capabilities: Lead the design and evolution of scalable engineering platforms, products, and shared services. Architect reusable APIs, SDKs, frameworks, and self-service capabilities. Establish platform standards, patterns, and engineering practices. Drive platform modernization and cloud-native adoption. Implement governance guardrails for secure, compliant software delivery. Partner with teams to deliver enterprise solutions and improve developer experience.
• Intelligent Automation, AI Enabled Engineering: Lead development of intelligent automation solutions across the AI-Driven Development Lifecycle. Architect scalable automation frameworks, AI services, and platform capabilities. Drive adoption of automation-first and AI-assisted engineering practices. Design automation for development, testing, deployment, operations, governance, and security. Lead implementation of AI agents and intelligent workflows. Collaborate with teams to embed automation across engineering ecosystems.
• AI Engineering & Agent Platforms: Lead development of AI-powered engineering capabilities, autonomous workflows, and developer experiences. Architect and implement AI agents, orchestration frameworks, and agent-based solutions. Integrate LLMs, prompt engineering, context engineering, MCP, and RAG capabilities. Define standards and best practices for AI-enabled engineering. Evaluate emerging AI technologies and establish scalable adoption patterns.
• Developer Experience & Self-Service Engineering: Lead initiatives that improve developer experience through self-service platforms and enablement capabilities. Define standards and best practices for developer workflows. Build reusable templates, accelerators, and automation assets that increase efficiency. Drive platform adoption through technical leadership and enablement. Enhance engineering workflows using feedback and operational insights. Advocate developer-centric platform design and engineering excellence.
• Platform Operations, Reliability & Delivery Enablement: Lead integration of platform capabilities into engineering workflows, CI/CD pipelines, and operations. Design highly available, resilient, scalable, and observable platform solutions. Define deployment standards, governance controls, and reliability practices. Implement observability, operational intelligence, anomaly detection, and automated remediation. Drive adoption of IaC, cloud-native architectures, and automation. Use operational metrics and insights to improve platform performance and reliability.
• Security, Governance & Engineering Controls: Design and implement platform-wide security controls and governance capabilities. Establish secure-by-design practices and automated compliance controls. Lead policy enforcement, risk management, and compliance automation solutions. Define technology guardrails that balance agility and governance requirements. Partner with security, risk, and architecture teams to align with organizational standards. Continuously improve security through automation and proactive engineering initiatives.