AI Engineer

🕒 January 12

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 76%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Opplane

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

🤖 Artificial Intelligence

💳 Fintech

☁️ SaaS

🔥 Funding within the last year

💰 Accelerator/Incubator on 2025-12

Artificial Intelligence • Fintech • SaaS

Opplane is a software company that helps organizations unlock the value of data through connectivity, data governance, and generative AI. It focuses on applying AI-driven data solutions to regulated environments, especially banking and fintech, enabling compliance, secure data connectivity, and AI use cases for financial services and enterprises.

📋 Description

• Build and orchestrate LLM agents using Gemini Pro and LangChain • Design, implement, and operate RAG solutions at scale • Integrate with Gemini and Vertex AI services using API-driven architectures • Debug and optimize end-to-end LLM pipelines, including: chunking strategies, embeddings, retrieval logic, LLM response behavior • Deliver production-ready AI services, including monitoring, rate limiting, and reliability controls • Participate in solution design and technical decision-making • Continuously evaluate and experiment with new LLM models and features as they become available • Implement AI safety, security, and compliance controls across the AI lifecycle • Collaborate with cross-functional teams across time zones

🎯 Requirements

• Strong AI Engineer / Senior Individual Contributor • Hands-on experience integrating Gemini Pro 1.x via API endpoints • Strong experience building LLM agents using LangChain or similar frameworks • Advanced understanding of prompt engineering and agent orchestration • Proven ability to debug end-to-end LLM systems, including chunking, embeddings, retrieval, and generation layers • Hands-on experience with vector databases (Pinecone, Chroma, FAISS) • Strong understanding of RAG architectures at scale • Practical knowledge of RAG evaluation metrics, including: Precision@K, Recall@K, MRR, nDCG, Faithfulness and Answer Relevance • Strong hands-on experience with Google Cloud Platform, including: Storage services, Serverless compute, Search, Transcription, Chat / conversational services • Practical experience in multi-cloud environments • Working experience integrating AWS services alongside GCP • Excellent programming skills in Python, PySpark, or Java • Strong experience building scalable, API-based AI solutions • Solid understanding of API rate limiting, performance tuning, and reliability • Hands-on experience implementing AI safety and guardrails, including: Input validation, PII detection and redaction, Reliability and hallucination checks, Compliance controls • Knowledge of multi-layered security, including IAM, data isolation, and audit logging

🏖️ Benefits

• Competitive salary • Flexible working hours • Professional development budget • Home office setup allowance • Global team events

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