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Position: Data Engineer - AWS AI Location: Pune/Nagpur/Chennai/Bangalore Type of Employment: Full-time Purpose of the Position: This role is ideal for individuals who are passionate about applying their expertise in AI Engineering, Data Engineering, programming, data analysis, and problem-solving to real-world challenges. As a key member of our engineering team, you will support clients on their AI journey by developing solutions that drive measurable business value. This position plays a critical role in advancing Infocepts strategic goals by delivering data-driven insights and enabling transformative AI/ML programs. Key Result Areas and Activities: Data & Cloud Engineering: Design and maintain high-performance ETL/ELT pipelines on AWS using PySpark, Python, SQL across EMR, Glue, Lambda, Step Functions, Redshift, and S3. Applied AI LLM, RAG, Agentic Workflows: Develop, fine-tune, and deploy LLMs (GPT 4 class, BERT, T5) for enterprise applications. Implement RAG using FAISS, Elasticsearch, LangChain, LlamaIndex, or similar frameworks for grounding, vector search, and knowledge retrieval. AI Platform & Tooling (Modern Stack): Work with emerging enterprise AI platforms including: Snowflake Cortex for secure LLM inferencing, embeddings, and feature pipelines Databricks Lakehouse AI / Databricks Genie for model training, inference, and agentic workloads. Architecture, Governance & Collaboration: Contribute to solution architecture, AI governance, data security, and model lifecycle frameworks. Essential Skills: Expert-level skills in Python, PySpark, Scala and advanced SQL. Hands-on experience with AWS (EMR) services. Working experience with LLMs, RAG, vector databases, and transformer-based architectures. Solid understanding of distributed systems, data modeling, and data platform design. Desirable Skills: Experience with Snowflake Cortex for secure enterprise LLM workloads. Experience with Databricks Genie / Lakehouse AI, Unity Catalog, Delta Live Tables. Good functional knowledge of Media & Entertainment domain. Knowledge of prompt engineering, safety guardrails, and agent tooling. Familiarity with feature stores, model registries, MLflow, or similar tooling. Knowledge of statistical methods, deep learning, NLP techniques. Qualifications: 3+ years of experience across AI/ML and Data Engineering. Bachelors degree in computer science engineering, or related field (masters degree is a plus) Qualities" Strong collaboration across cross-functional and cross-time-zone teams. Persuasive communicator with strong presentation and storytelling skills. Location Pune, Maharashtra, India Years Of Exp 3 to 7 years .
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.