Senior AI Engineer – Gemini, Vertex AI

Job not on LinkedIn

🕒 January 13

🇮🇳 India – Remote

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 76%

What it means: how likely this posting is sitting open without active hiring.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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DKSH Portugal, Unipessoal, Lda.

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2014

🍽️ Food & Beverage

📦 Logistics

💼 Consulting

Food & Beverage • Logistics • Consulting

DKSH Portugal, Unipessoal, Lda. is the Portuguese operation of DKSH, a global market‑expansion services provider that helps multinational companies distribute, market and sell specialty chemicals, ingredients (food & beverage, personal care), pharmaceuticals and performance materials. The company offers end‑to‑end B2B services — including distribution, marketing, sales, logistics and regulatory support — to help partners grow their presence in Portugal and connect local markets with global brands.

📋 Description

• We are seeking a Lead AI Engineer with deep, hands-on experience in Gemini, Vertex AI, and multi-cloud GenAI platforms to deliver production-grade LLM and RAG solutions at scale. • This is a delivery- and implementation-focused role, with ownership across solutioning, development, and operationalization of AI systems. • The role requires strong hands-on coding, architectural thinking, and the ability to adapt as AI technologies evolve rapidly. • 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

• GenAI & LLM Engineering • 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 • RAG & Vector Search • 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 • Solid grasp of vector similarity search fundamentals • Cloud & Multi-Cloud • 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 • Programming & APIs • 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 • AI Safety, Security & Compliance • 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. • NICE-TO-HAVE Skills (Strong Plus) • Experience using Terraform or Infrastructure-as-Code tools • Background in data analytics, data engineering, or data science • Knowledge of data warehousing concepts (ETL/ELT, analytics platforms) • Experience evaluating and comparing new LLM models as they enter the market • Exposure to bias mitigation techniques in enterprise AI systems • Experience operating large-scale production RAG systems.

🏖️ Benefits

• Global & Multicultural – Our team unites professionals from around the world, blending diverse ideas and experiences that fuel innovation. • Startup Energy – We move fast, embrace change, and turn ideas into action in a dynamic and high-impact environment. • Empowered Ownership – Each team member owns their work and contributes directly to our collective success. • Collaborative & Friendly – We foster an open, approachable culture where collaboration and curiosity thrive.