1 day ago
Bengaluru, IndiaStaff+
Responsibilities
- Design, develop, and deliver production-grade AI/ML software solutions and enterprise AI capabilities.
- Own AI subsystems including agentic workflows, LLM applications, evaluation pipelines, MLOps tooling, and model-serving platforms.
- Build scalable, secure, maintainable APIs, microservices, and multi-step AI workflows for high-throughput, low-latency workloads.
- Develop and optimize prompt engineering, RAG architectures, agent orchestration, tool use, planning, and memory systems.
- Design and implement distributed systems using cloud platforms, event-driven architectures, containers, and orchestration environments.
- Establish evaluation, benchmarking, monitoring, observability, safety, governance, and security controls for AI systems.
- Collaborate with product managers, designers, engineers, and business stakeholders from system ideation through completion.
- Lead technical delivery, mentor junior engineers, participate in code reviews, and guide team members through complex assignments.
- Manage operational risk, strengthen controls, and contribute to technology policies and governance.
Requirements
- Bachelor's degree or above in Computer Science, Engineering, Mathematics, or a related discipline.
- 8+ years of software engineering experience, including at least 3 years building AI/ML systems, scalable ML infrastructure, or enterprise-scale model-serving platforms.
- Strong proficiency in Python with FastAPI and asyncio, and/or Go or Java, with production API and microservices experience.
- Hands-on experience developing agentic AI systems and LLM applications, including multi-agent orchestration, tool use, planning frameworks, and multi-step workflow deployment.
- Experience with prompt engineering, RAG architectures, Strands, LangGraph, Google ADK, model serving with vLLM, and OpenAI-compatible APIs.
- Strong understanding of distributed systems, microservices, cloud platforms, API design, and event-driven architectures.
- Experience with AWS services including EC2, EKS, S3, IAM, RDS, and an AI service such as Bedrock or SageMaker.
- Hands-on experience with Docker, Kubernetes, CI/CD pipelines, CloudFormation, Terraform, OpenTelemetry, and distributed tracing.
- Ability to work independently on system design from ideation through completion and communicate with technical and non-technical stakeholders.
- Preferred experience with agent evaluation and benchmarking, reasoning traces, vector databases, knowledge graphs, semantic search, memory systems, and retrieval optimization.
- Preferred experience implementing AI safety controls such as content filtering, guardrails, prompt-injection detection, and PII redaction.
- Knowledge of NIST AI RMF, MITRE ATLAS, OWASP LLM Top 10, responsible AI, model governance, Zero Trust architecture, EntraID, OAuth2/OIDC, and financial-services regulations.
- Familiarity with LoRA, RLHF, supervised fine-tuning, domain-specific SLMs, GPU workload management, and inference optimization.
Benefits
- The role is based in Barclays offices in Bengaluru and Pune.
- The position offers technical leadership and mentoring opportunities within Barclays' AI and technology organization.
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About Barclays
Barclays is a UK‑based universal bank that provides retail and commercial banking, credit cards (Barclaycard), wealth management, and investment banking to consumers, businesses, and institutions. Publicly listed in London and New York, it generates revenue from net interest income, fees, and markets activities, and operates across Europe, the Americas, the Middle East, and Asia. Founded in 1690 and headquartered in London, it serves customers through digital channels and a branch network.