15 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Architect and build custom AI infrastructure and hardware solutions while optimizing performance, power consumption, cost, and scalability.
- Design and implement LLM application components, prompts, tools, agents, orchestration flows, memory and context handling, retrieval pipelines, and evaluation harnesses.
- Build AWS-based agent workflows, enterprise API integrations, secure RAG systems, ingestion and retrieval workflows, and AI platform integrations.
- Implement safety and control features including PII detection and redaction, prompt-injection defenses, content filters, guardrails, authentication, authorization, lineage, and audit logging.
- Collaborate with architects, data engineers, product owners, and security stakeholders to deliver tested, observable, maintainable software components.
- Maintain component designs, integration specifications, deployment runbooks, evaluation results, and reusable engineering patterns.
Requirements
- A bachelor’s degree in Computer Science, Computer Engineering, Data Science, AI/ML, Information Technology, or a related engineering discipline.
- At least 5 years of software, data, or AI engineering experience, including cloud-native engineering and GenAI, LLM, NLP, or agentic AI delivery experience.
- Hands-on Python coding experience and strong understanding of APIs, distributed systems, testing, observability, secure SDLC practices, and CI/CD.
- Experience with Amazon Bedrock, Bedrock Agents or AgentCore, Knowledge Bases, Guardrails, Lambda, API Gateway, Step Functions, OpenSearch, SageMaker, IAM, CloudWatch, CloudTrail, VPC, KMS, and S3.
- Understanding of RAG, function and tool calling, agent orchestration, model invocation, prompt engineering, embeddings, vector databases, and evaluation metrics.
- Experience implementing AI/ML and GenAI components across data ingestion, preparation, model integration, deployment, monitoring, and continuous improvement.
- Experience delivering AI/ML or data products in an industry domain such as banking, insurance, healthcare, retail, telecom, or capital markets.
- Experience with Git-based development, automated testing, CI/CD pipelines, infrastructure as code, and client-facing delivery.
- Preferred experience includes AWS Solutions Architect or Machine Learning Specialty certification, CDK or Terraform, EKS, Amazon Q, responsible AI controls, FinOps, LangChain, LangGraph, LlamaIndex, Haystack, MLflow, FastAPI, Docker, and Kubernetes.
- Preferred knowledge includes responsible AI, model risk management, synthetic data generation, human-in-the-loop review, A/B testing, and GenAI cost optimization.
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About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.