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Telangana · On-site · 5-8 Yrs · Oct 20
1 views
Accounting & Tax · 10000+ Employees · New York, US
11 open roles1 posted in 7d11 in 30d
Work-life balance 2.9Compensation & benefits 3.3Culture & values 3.5
Hiring: Engineering
What employees say
+ You get to learn a lot there, and I had an opportunity to work in the client location.
− Career and financial growth is slower.
More reviews on the company profile.
Interview experience · Summer Associate
2 interviews and an HR round Had one case interview and one interview about Indian defense Policy and strategy The case interview had 2 parts with one small presentaion towards the end The HR round was standart more l
Average difficulty · Bengaluru · 2,675 reports
More interview insightsJob description
Overview
Additional Job Description
Responsibilities
- 4+ year of experience working with AI solutions
- Design and implement Generative AI solutions leveraging large language models, Retrieval-Augmented Generation architecture patterns, semantic search, knowledge graphs, and enterprise knowledge integration.
- Implement Agentic AI solutions, including autonomous AI workflows, multi-agent orchestration, agentic frameworks, tool integration, guardrails, and human-in-the-loop controls for enterprise use cases.
- Establish prompt engineering, prompt management, evaluation, versioning, reuse, and lifecycle practices for scalable Generative AI delivery.
- Drive adoption of DevOps and MLOps practices, including CI/CD, infrastructure as code, automated testing, model deployment automation, monitoring, alerting, and release governance.
- Implement responsible AI and AI governance practices, including AI risk assessments, model explainability, transparency, validation, monitoring, and regulatory readiness for AI systems.
- Ability to support technical configuration activities including group and security configuration, database rules, validations, calculation logic, and reference data definition
- Python: Strong hands-on Python experience, including async (asyncio/anyio), type hints, and Pydantic v2. Experience building FastAPI services with versioned API contracts.
- LLM application development: Hands-on experience building LLM applications with Pydantic AI or similar frameworks. Includes typed, schema validated outputs and handling malformed model responses through retries, repair, and fallbacks.
- Workflow orchestration: Experience building multi-step LLM pipelines with LangGraph.
- Document AI: Extracting data from PDFs, scans, images, and Word files using OCR (Tesseract, PaddleOCR) and PDF tooling (PyMuPDF, pypdf). Includes deciding when to use native text and when to use OCR.
- LLM evaluation: Building ground-truth datasets, field-level scoring, baseline comparisons, and CI regression gates, so prompt and model changes are measured, not guessed.
- Prompt engineering: Designing, versioning, and tuning prompts for accuracy, token cost, and latency.
- LLM security: Mitigating prompt injection, handling untrusted input safely, and returning safe error responses.
- Production delivery: A track record of shipping GenAI systems to production. Sound judgment on trade-offs between quality, latency, cost, and scalability, including batching, retries, confidence thresholds, and routing to human review.
- Docker and Kubernetes (Helm, GitOps), plus CI/CD with GitHub Actions.
- Testing with pytest, including fixture-driven tests and mocked LLM clients.
- Integrating with enterprise workflow platforms such as Appian, or other downstream systems with strict API contracts.
- Observability for LLM calls, including tracing and token, and cost tracking.
- A cloud AI/ML certification, such as Microsoft Azure AI Engineer Associate, AWS Certified Machine Learning Engineer Associate, or Google Cloud Professional Machine Learning Engineer
- Certified Kubernetes Application Developer (CKAD)
- Databricks Certified Generative AI Engineer Associate, or a similar vendor GenAI certification
- Minimum Degree Required: B.E/B.Tech
- Minimum Years of Experience: 5-8 Years
- Strongly preferred:
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Last updated 27 October 2026
- How do I apply for Gen AI Engineer at PWC?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. PWC may attach structured assessments to interview rounds after you apply.
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- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is Gen AI Engineer remote or on-site in Telangana?
- This listing is marked on_site with location Telangana. Confirm details on the job description before applying.
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- This is a mid-level Gen AI Engineer role. Key skills include skills listed in the job description. Feedback AI highlights matched vs missing skills on your profile after signup.