G42Principal Software Engineer
AI in this role
Inception42, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inception42.ai
Overview:
We are seeking a highly accomplished Principal Software Engineer to lead end-to-end technical strategy, architecture, and execution across web-scale, platforms. This individual will be instrumental in defining system-level patterns, enforcing engineering best practices, and mentoring senior engineers within a fast-paced, agile environment. Will be leading our critical components of our AI platform and provide technical leadership across projects.
Responsibilities:
- Architect and build scalable platform systems (frontend platforms, backend services, and shared infrastructure)
- Develop reusable UI frameworks, design systems, and component libraries
- Design and maintain platform APIs and shared services used across multiple products
- Establish and drive platform engineering best practices (modularity, observability, reliability, and security)
- Build and optimize CI/CD pipelines, internal developer platforms, and automation tooling
- Improve developer experience (DevEx) by reducing friction in development, testing, and deployment
- Ensure high availability, performance, and scalability across distributed systems
- Mentor engineers and guide teams in adopting platform capabilities effectively
Qualifications:
To qualify for the role, you must have
- 12–15+ years of experience in software engineering with strong full stack and platform engineering expertise
- Strong experience building shared platforms, frameworks, or internal tooling
- Proficiency in front-end technologies (React, Angular) and modern JavaScript/TypeScript
- Strong backend experience (Node.js, Python, or Go) with API and service design at scale
- Deep understanding of distributed systems, microservices, and platform architectures
- Experience with API design (REST/gRPC), service contracts, and versioning strategies
- Strong experience with cloud platforms (AWS, Azure) and platform-native services
- Hands-on experience with Docker, Kubernetes, and orchestration at scale
- Experience with observability tools (monitoring, logging, tracing) is a plus
AI & Agentic Systems Expertise:
- Experience designing and building AI agent workflows and orchestration systems
- Familiarity with LLM-based applications, prompt design, and tool-augmented agents
- Experience integrating AI agents with APIs, services, and enterprise workflows
- Understanding of agent frameworks (e.g., LangChain, Semantic Kernel, or similar)
- Experience with multi-agent systems, task planning, and workflow automation
- Knowledge of evaluation, guardrails, and reliability patterns for AI systems
- Exposure to RAG pipelines, vector databases, and context management is a plus
How we rate this
Principal Software Engineer at G42 rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What's a project where you used LangChain hands-on?
- Walk me through how you've used Semantic Kernel in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, RAG, AI Agents, LangChain, and Semantic Kernel. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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