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Join Barclays as a Lead AI Engineer role, where you will design and build core AI/ML solutions that power our enterprise AI capabilities. You will take ownership of significant AI subsystems from agentic workflows and LLM applications to evaluation pipelines and MLOps tooling delivering production-grade solutions that are secure, scalable, and aligned with our architectural vision. You bridge the gap between AI architecture and hands-on implementation, driving technical delivery while mentoring junior engineers. At Barclays, we don't just anticipate the future - we're creating it. To be successful in this role, you should have below skills: Bachelor's degree (or above) in Computer Science, Engineering, Mathematics, or related discipline 8+ years software engineering experience with at least 3 years building AI/ML systems, scalable ML infrastructure, or model serving platforms at enterprise scale Strong proficiency in Python (FastAPI, asyncio) and/or Go/Java, with production experience building APIs and microservices serving high-throughput, low-latency workloads Hands-on experience developing agentic AI systems and LLM applications including multi-agent orchestration, tool use, planning frameworks, and deployment of multi-step AI workflows Solid technical knowledge of prompt engineering, RAG architectures, and modern agentic frameworks (Strands, LangGraph, Google ADK) with ability to build and optimise agent-based solutions Working experience with GenAI/LLM systems prompt engineering, retrieval-augmented generation, model serving (vLLM), and OpenAI-compatible API surfaces Strong understanding of distributed systems architecture microservices, cloud platforms, API design (REST, gRPC, OpenAPI), and event-driven architectures Experience with AWS services EC2/EKS, S3, IAM, RDS, and at least one AI service (Bedrock, SageMaker) Hands-on experience with Docker and Kubernetes containerising applications and deploying to orchestrated environments Experience with CI/CD pipelines, Infrastructure-as-Code (CloudFormation, Terraform), and observability tools (OpenTelemetry, distributed tracing) Ability to work on system design from ideation through completion with limited supervision; effective communication with both technical and non-technical stakeholders Some other highly valued skills may include below: Experience building evaluation frameworks for agentic systems including agent benchmarking, reasoning traces, and monitoring observability for multi-step AI workflows in production Experience in vector databases, knowledge graphs, semantic search, and memory systems for stateful agents with understanding of retrieval optimisation and context management Experience implementing AI safety controls content filtering, guardrails, prompt injection detection, PII redaction Knowledge of AI security frameworks NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10 Familiarity with model fine-tuning techniques (LoRA, RLHF, supervised fine-tuning) for domain-specific SLMs Knowledge of responsible AI practices, model governance, and security considerations for autonomous systems Understanding of Zero Trust architecture and identity systems (EntraID, OAuth2/OIDC) Background in financial services understanding of regulatory requirements, data residency, and compliance obligations Experience with GPU workload management and inference optimisation (vLLM) You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role is based in Bengaluru and Pune office. Purpose of the role To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. Accountabilities Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance.Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives.Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.Stay informed of industry technology trends and innovations and actively contribute to the organizations technology communities to foster a culture of technical excellence and growth.Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.Implementation of effective unit testing practices to ensure proper code design, readability, and reliability. Assistant Vice President Expectations To advise and influence decision making, contribute to
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.