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Apprentice, Software Engineer
Bangalore, IND
Workplace Type: Hybrid
Job: Engineering
Schedule: FULL_TIME
Req ID: 23305
Role Title: Apprentice - AgentOps Engineering
Tier: IC10
Department/Division: OCTO
Location: – On-site
Employment Type: Full-time Apprenticeship
Stipend: ₹30,000 per month
Duration: 12 months
Target Start Date: 1-Apr-2026
Number of Roles: 2
About Pearson
Pearson is the world’s leading learning company, dedicated to helping people make progress in their lives through learning. Founded in 1844, we deliver digital-first, accessible learning experiences and employ over 20,000 people globally. In India, we support learners and educators through innovative educational products, technology, and services. We are committed to fostering an inclusive, equitable workplace where every employee is valued and empowered to thrive.
About the Apprenticeship Program
Pearson India’s Apprenticeship Program provides graduates and early-career professionals with structured training, hands-on experience, and mentorship from industry experts. Through a blend of on-the-job learning and guided development, apprentices build the professional and technical skills needed to succeed in a global organization.
About the Team
AgentOps is a strategic enterprise capability focused on building, operating, and governing AI agents as first-class production systems across Pearson. The team enables a symbiotic workforce where employees and AI agents work together to accelerate outcomes, improve quality, and deliver measurable business value while maintaining high standards of trust, governance, and compliance.AgentOps operates across multiple integrated streams including Agentic Automations, Agentic Applications, and Agentic Engineering. The team delivers production-grade agentic solutions that modernize critical business workflows such as document processing, decision tracking, content quality assurance, and executive operations.
About the Role
As an AgentOps Engineering Apprentice, you will work closely with experienced engineers, product leaders, and AI practitioners to design, build, test, and operate enterprise-grade AI agents and agentic applications. This role is designed for recent graduates who are eager to gain hands-on experience with modern software engineering, cloud platforms, and emerging agentic AI technologies.
The apprenticeship is learning-focused and hands-on. Apprentices contribute to real production initiatives while developing strong foundations in software engineering best practices, system reliability, and responsible AI.
Key Responsibilities
Assist in building and enhancing agentic applications and intelligent automations that support real business workflows across Pearson.
Work with senior engineers to develop reusable AI agents using approved frameworks and the AgentOps orchestration platform.
Participate in solution design discussions, intake reviews, and engineering reviews to understand how enterprise AI solutions are designed and governed.
Support implementation of observability, logging, testing, and evaluation mechanisms to ensure agent quality, reliability, and safe behavior.
Contribute to documentation, testing, and continuous improvement of agentic solutions.
Learn and adhere to AI policy, security, privacy, and compliance guardrails while working on production systems.
Required Qualifications
Final-year engineering student or recent graduate with a Bachelor’s degree in Computer Science, Engineering,.
Strong knowledge in Python and any of the Agentic Frameworks
Solid understanding of data structures, algorithms, and basic software engineering concepts.
Strong problem-solving skills and a willingness to learn new technologies.
Exposure to AI/ML concepts, large language models
Interest in Agents,AI, automation, and modern cloud-based systems.
Preferred / Nice-to-Have Skills
Understanding of APIs, microservices, or cloud platforms.
Familiarity with Git, CI/CD pipelines, agile development practices.
Interest in responsible AI, platform engineering, or system reliability.
Eligibility Criteria
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field
Recent graduates or candidates with less than one year of experience are encouraged to apply.
Must meet requirements under the Apprenticeship Act, 1961 and be registered on the NATS portal.
Must be legally eligible to work in India.
Experience You Will Gain
Hands-on experience building and operating enterprise AI agents.
Exposure to production-grade AI systems, governance, and observability practices.
Structured mentorship from senior engineers operating in a player-coach model.
Opportunities for continuous learning, upskilling, and certification aligned with AgentOps engineering standards.
Location
This role is based at the Pearson office at – Bangalore
Diversity, Equity, and Inclusion
Pearson India is committed to building an inclusive environment that embraces diverse perspectives and backgrounds. We value equality, respect, and belonging, ensuring every employee has the opportunity to contribute and grow.
Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are
As a Apprentice, Software Engineer at Pearson, you will be at the forefront of solving complex problems that impact millions of users. This is not just about writing code or executing tasks; it is about taking ownership of critical systems, collaborating with top-tier talent, and driving innovation. If you want a role that challenges you to grow rapidly and leaves a lasting impact on the industry, this is it.
To stand out for this position, you need more than just the basics. Hiring managers for this Apprentice, Software Engineer role are looking for:
Pearson is hiring for Apprentice, Software Engineer in Hybrid Bangalore. This page goes beyond the raw listing so students can understand what the role usually expects, how to prepare for screening, and how to apply more thoughtfully instead of forwarding a resume blindly.
Pearson appears on Campus to Career because the opportunity is relevant for students and early-career candidates who want a clearer view of real hiring demand. When evaluating any employer, students should look beyond the brand name and focus on work quality, reporting structure, product maturity, mentorship, and the kind of ownership the team is likely to trust a new hire with.
A fresher or internship role at Pearson can be valuable when the candidate understands what the business is solving and how the team contributes to that larger outcome. Even before the interview, students should try to learn the company domain, customer type, pace of execution, and whether the role sits close to product, platform, support, data, or delivery.
Apprentice, Software Engineer is likely not just a keyword match. In real hiring, titles often compress multiple expectations into one label. This means the student should read the listing as a signal of day-to-day problem solving, team collaboration, deadline discipline, and the ability to learn new workflows quickly.
The current role is listed as Internship in Hybrid Bangalore, with Fresher / 0-1 Years mentioned on the page. For freshers, the most useful interpretation is: what kind of output will the team expect in the first 30 to 90 days, and what proof can the candidate show that they are ready to deliver it?
The listing highlights skills such as Python, Agentic Frameworks, Data Structures, Algorithms, Software Engineering, AI, ML, APIs. Students should not panic if they are not equally strong in every item. Companies often list an ideal stack, but interviewers usually look for transferable understanding, clarity of fundamentals, and a believable proof-of-work story.
A better preparation strategy is to sort skills into three buckets: already strong, interview-ready but shallow, and currently weak. This prevents overconfidence and also stops students from wasting time revising topics that are unlikely to matter during the first screening round.
Students should treat eligibility as more than just degree, batch, or marks. Real readiness also includes whether the resume supports the role clearly, whether your GitHub or portfolio can survive a quick recruiter scan, and whether your self-introduction makes logical sense for Apprentice, Software Engineer.
If the listing mentions a batch requirement, relocation, internship-to-full-time path, or communication expectations, make sure those details are reflected consistently in your resume, application form, and outreach message. Consistency is a major trust signal in early-stage screening.
The listing currently mentions compensation as ₹30,000 per month. Students should still verify fixed pay, bonus, internship stipend, ESOPs, and location-based cost differences on the official employer page or in HR discussions.
For freshers, salary should be interpreted together with learning quality, tech exposure, mentorship, workload, location, and conversion or growth path. A slightly smaller offer with stronger ownership and cleaner learning loops may outperform a bigger offer that provides weak role fit or no meaningful skill depth.
Candidates applying for Apprentice, Software Engineer should prepare in layers. The first layer is role fit: why this company, why this role, and what proof supports your application. The second layer is technical or functional depth: the tools, concepts, or workflows most likely to appear in screening. The third layer is behavior and communication: clear explanations, honest ownership, and calm thinking when details are incomplete.
A strong practice method is to prepare a short project walk-through, a role-fit introduction, one debugging or challenge story, and a realistic answer to what you still want to learn. That combination usually performs better than memorizing long theoretical scripts.
The best candidates do not just click apply. They adapt. Before submitting, update the top section of your resume, reorder projects if needed, and make sure your strongest evidence matches the narrative for Apprentice, Software Engineer. If the company uses an external portal, take form fields seriously because ATS filters often read those signals separately from the PDF.
If the route is recruiter email or a direct apply link, use that path professionally. Submit complete information, avoid spammy follow-up, and if you choose to reach out on LinkedIn, mention the role, one or two fit points, and a respectful ask. The goal is to make your application easier to trust, not louder.