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About This Role
We are Progress (Nasdaq: PRGS) \- the trusted provider of software that enables our customers to develop, deploy and manage responsible, AI\-powered applications and experiences with agility and ease.
We’re proud to have a diverse, global team where we value the individual and enrich our culture by considering varied perspectives because we believe people power progress. Join us as an IT Software Engineer Intern (Recent Graduate) – Salesforce \& AI Solutions and help us do what we do best: propelling business forward. This will be a hybrid so working between your home office and either our Burlington MA headquarters or Raleigh NC office. You must be local to one of those at time of application as we can not provide any relocation packages.
We are looking for highly motivated recent graduates to join our IT Engineering team through a three\-month internship program focused on Salesforce development, enterprise solution delivery, automation, and AI\-enabled innovation. This is a paid hourly internship designed as a pathway into a full\-time engineering career, with the intent to convert high\-performing interns into regular full\-time team members following the internship period.
This is an outstanding opportunity for early\-career engineers who want hands\-on experience solving real business problems using modern enterprise technologies, automation platforms, and AI\-powered engineering practices. Interns will work directly with experienced technical leaders and business stakeholders while gaining exposure to enterprise application development, system integrations, Agile delivery, DevOps concepts, and practical AI implementation across the software development lifecycle.
AI will be a core part of the day\-to\-day engineering experience in this role. Interns will be expected to leverage AI tools and intelligent automation technologies throughout development activities — including coding, testing, troubleshooting, analysis, documentation, and workflow optimization — while also contributing to AI\-powered applications, agents, copilots, and automations that interact with Salesforce data and business processes.
While prior Salesforce experience is a plus, it is not required. We are looking for intellectually curious, technically strong, adaptable problem\-solvers who are excited to learn quickly, work collaboratively, and help shape the future of AI\-enabled enterprise software engineering.In this role, you will:
- Partner with business teams to understand challenges, gather requirements, and help design scalable technology solutions that improve business operations and user experiences
- Build, enhance, and support applications, automations, workflows, integrations, and user experiences within the Salesforce ecosystem
- Leverage AI tools and intelligent automation technologies as part of your daily software engineering workflow — including coding, testing, debugging, troubleshooting, documentation, analysis, and solution optimization
- Develop and evolve AI\-powered solutions, agents, copilots, and automations that interact with Salesforce data and business processes to improve efficiency and user productivity
- Contribute to the design and implementation of scalable AI\-enabled workflows and operational automations for internal teams and business users
- Support Agile\-based software delivery across the full software development lifecycle, including design, development, testing, deployment, monitoring, and continuous improvement
- Work with APIs, integrations, and enterprise platforms to connect systems and enable seamless data and workflow orchestration
- Collaborate closely with engineering, IT, operations, and business stakeholders in a highly iterative and innovation\-focused environment
- Continuously evaluate emerging AI capabilities, engineering tools, and automation opportunities to help modernize development practices and accelerate delivery
- Learn and apply enterprise software engineering best practices, architecture patterns, DevOps concepts, and scalable platform development techniques
Technologies \& Areas You May Work With
- AI\-enabled workflows, copilots, and intelligent automation tools (e.g. Salesforce Agentforce/Einstein, Microsoft Copilot, Github Copilot CLI)
- Salesforce Lightning Platform \+ Lightning Web Components (LWC)
- Apex, APIs, integrations and web services
- Salesforce Service Cloud, Sales Cloud, and Experience Cloud
- Automation tools and Lightning Flows
- Agile development methodologies and DevOps concepts
- Collaboration and delivery platforms such as Jira, Asana and related tools
Your background:
- Recent graduate (or graduating Summer 2026\) with a degree in Computer Science, Software Engineering, Industrial Engineering, Information Systems or a related technical discipline
- Strong analytical thinking and problem\-solving skills
- Passion for technology, software engineering, automation, and AI.
- Practical AI implementation experience (internship, work, school, personal)
- Ability to communicate effectively with both technical and business audiences
- Demonstrated curiosity, initiative, and willingness to learn quickly
- Experience from internships, research projects, hackathons, student organizations, or personal projects is highly valued
- Exposure to programming, scripting, APIs, databases, or cloud technologies is required
- Interest in enterprise platforms and business process optimization
Additionally, it would be beneficial if you have:
- Exposure to Salesforce, CRM systems, or cloud platforms
- Experience building AI\-powered applications, automations, or agents
- Understanding of Agile development concepts
- Salesforce certifications or Trailhead coursework
Pay transparency: this role will be paying $28\.00\-35\.00 an hour.
If this sounds like you and fits your experience and career goals, we’d be happy to chat.What we offer in return is the opportunity to experience a great company culture with wonderful colleagues to learn from and collaborate with.
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\#LI\-hybrid
Salary Context
This $58K-$72K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $190K across 219 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 3,823 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Progress, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $232,000 based on 797 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $97,880. This role's midpoint ($65K) sits 72% below the category median. Disclosed range: $58K to $72K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Progress AI Hiring
Progress has 1 open AI role right now. They're hiring across AI Software Engineer. Based in Raleigh, NC, US. Compensation range: $72K - $72K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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