Job Opportunity: Software Engineer II – Generative AI & LLM Platforms

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an office.

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Overview

Are you passionate about cutting-edge technology and eager to contribute to the development of secure and scalable Generative AI products and platforms? We are seeking a Software Engineer II to join our team and help shape the future of AI-driven solutions. In this role, you will collaborate with experienced engineers to design, develop, test, and operate innovative systems leveraging large language models (LLMs), retrieval-augmented generation (RAG), vector databases, cloud technologies, and distributed systems.

If you have a strong foundation in software development, a curious mindset, and a desire to grow your expertise in Generative AI, this is the perfect opportunity for you.

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Responsibilities

• Design and implement limited enhancements, updates, and programming changes for portions and subsystems of systems software, including operating systems, compilers, networking, utilities, databases, and Internet-related tools.
• Analyze design requirements and determine coding, programming, and integration activities based on specific objectives and established project guidelines.
• Execute and write portions of testing plans, protocols, and documentation for assigned applications; identify and debug issues with code and suggest improvements.
• Collaborate with internal and outsourced development partners to develop reliable, cost-effective, and high-quality solutions for assigned systems or subsystems.
• Participate in project teams, contributing to design discussions, code reviews, and issue resolution.

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Qualifications

Education and Experience Required:

• Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline.
• Typically 2-4 years of relevant experience.

Knowledge and Skills:

• Foundational software development knowledge gained through academic projects, internships, training, open-source contributions, or equivalent hands-on experience.
• Basic proficiency in Python, Golang, or a similar programming language, with an understanding of APIs, testing, debugging, version control, and core software design principles.
• Awareness of Generative AI and large language model concepts such as prompts, tokens, embeddings, context, inference, and common limitations, with an interest in developing deeper expertise.
• Basic understanding of cloud concepts and services, preferably AWS, including compute, storage, identity and access management, monitoring, and deployment fundamentals.
• Foundational networking knowledge, including TCP/IP, routing and switching basics, virtual networks, connectivity, network security, and systematic troubleshooting.
• Understanding of fundamental systems concepts such as scalability, reliability, security, performance, data management, and cost awareness.
• Ability to receive feedback, ask questions, share knowledge, participate constructively in design and code reviews, and collaborate with experienced engineers.
• Curiosity, a learning mindset, and a willingness to experiment with emerging technologies while adhering to established engineering, security, and quality practices.
• Ability to work in an agile team, break work into manageable tasks, build simple prototypes, communicate progress, and incorporate feedback into incremental improvements.

Preferred Qualifications:

• Cloud, Platform, and Network Architecture:
  • AWS cloud, Kubernetes, infrastructure as code, and CI/CD.
  • Amazon Bedrock and AWS AI/ML services.
  • Amazon EMR, Apache Spark, and Apache Flink.
  • Amazon Aurora PostgreSQL, pgvector, Amazon EKS, and Amazon S3.
• AI/ML Frameworks and Orchestration:
  • Hugging Face Transformers and PyTorch.
  • LangChain, LangGraph, and LlamaIndex.
• MLOps and LLMOps:
  • Experiment tracking, model registries, and version management.
• Security and Compliance:
  • Privacy-preserving AI and adversarial testing.
  • AI red teaming, content safety, and explainability.

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Day-to-Day

• Collaborate with team members to design and implement software components for Generative AI platforms.
• Write, test, and debug code to ensure high-quality, scalable, and secure solutions.
• Participate in agile ceremonies, including daily stand-ups, sprint planning, and retrospectives.
• Conduct code reviews and provide constructive feedback to peers.
• Experiment with emerging technologies and contribute to prototypes and proof-of-concept projects.
• Document technical designs, processes, and best practices.
• Support production systems, troubleshoot issues, and implement fixes as needed.

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Benefits

• Competitive salary and performance-based incentives.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and holidays.
• Professional development opportunities, including training and certifications.
• Access to cutting-edge tools and technologies.
• Collaborative and inclusive work environment.
• Opportunities to work on impactful projects that shape the future of AI.

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If you are ready to take the next step in your career and contribute to the development of innovative Generative AI solutions, we encourage you to apply today!