AI Summary
We are seeking an Applied ML Engineer (Gen AI) to establish and scale AI infrastructure and knowledge systems at NEXT Ventures. The ideal candidate will have technical depth in machine learning operations and creativity in applying AI to real-world business contexts. This role involves building robust LLM deployment pipelines, retrieval-augmented generation systems, and integrating AI agents into internal tools.
Key Highlights
Deploy and manage Large Language Models (LLMs) and build internal evaluation pipelines
Design and implement advanced retrieval-augmented generation pipelines and graph-powered knowledge systems
Develop scalable chunking and tokenization strategies for semantic search and document ingestion
Technical Skills Required
Benefits & Perks
Competitive salary
Bi-annual salary review
Festival bonus
Birthday leaves
Team events
Annual company retreats
In-house fitness trainer
Honeymoon package
Opportunities for relocation to Sri Lanka and Malaysia
Job Description
Who We Are
NEXT Ventures is where ambition takes shape and momentum becomes movement. As a global platform revolutionising access to performance-based capital, we empower the world’s most driven individuals to rise. Through our flagship brand, FundedNext, we empower dreamers to become doers, and potential to turn into performance. With 500+ driven minds across five countries, we power a global rhythm—220,000+ daily users from 170+ nations, each chasing greatness in their own way.
Your Role in Our Mission
The Applied ML Engineer (Gen AI) plays a foundational role in establishing and scaling the organization’s AI infrastructure and knowledge systems. This position focuses on building robust LLM deployment pipelines, retrieval-augmented generation (RAG) systems, embedding/tokenization workflows, and integrating AI agents into internal tools. The engineer will collaborate across teams to develop production-ready Gen AI applications and enable internal innovation at scale. The ideal candidate combines technical depth in machine learning operations with creativity in applying AI to real-world business contexts as well as a strong background in software engineering.
How You’ll Make An Impact
LLM Infrastructure & Evaluation
- Deploy, manage, and monitor Large Language Models (LLMs) such as LLaMA, GPT, Mistral, and Claude.
- Build internal evaluation pipelines to benchmark model performance across diverse business use cases.
- Design and implement advanced RAG pipelines using vector databases like Pinecone or Weaviate.
- Develop graph-powered knowledge systems using Neo4j, ArangoDB, or TigerGraph.
- Create scalable chunking and tokenization strategies for semantic search and document ingestion.
- Select and apply embedding models (OpenAI, Cohere, HuggingFace) for downstream tasks.
- Optimize chunking and retrieval pipelines for low-latency, high-recall performance.
- Engineer dynamic context windows for multi-turn conversations and long-form reasoning.
- Build autonomous workflows using LangChain, Haystack, AutoGen, or CrewAI.
- Integrate LLM tools into internal platforms (e.g., task bots, report generators, coding copilots).
- Automate tool use via Function Calling APIs and connect agents to knowledge graphs.
- Build CI/CD pipelines for data workflows, LLM retraining, and production rollout.
- Manage containerized environments using Docker, Kubernetes, or Kubeflow.
- Implement monitoring, alerting, and logging for Gen AI systems in production.
- Lead experiments and PoCs to evaluate new LLM use cases (chatbots, assistants, research agents).
- Collaborate with backend, data, and QA teams to scale AI solutions company-wide.
- Create reusable AI modules to support operational teams (e.g. Compliance, Finance, Payouts).
- Bachelor’s degree in Computer Science, AI, Data Engineering, or related field.
- Minimum 7 years of experience in relevant fields with 2+ years of experience in Machine Learning, MLOps, or AI infrastructure
- Proficiency in deploying and optimizing LLMs and vector databases.
- Hands-on experience with LangChain, LlamaIndex, or similar frameworks.
- Strong understanding of tokenization, embeddings, and prompt engineering.
- Experience with graph databases (e.g., Neo4j, ArangoDB) and query languages (Cypher, GraphQL).
- Familiarity with fine-tuning methods (LoRA, QLoRA) and feedback loops.
- Containerization and orchestration experience with Docker/Kubernetes.
- Team mindset, adaptability, and eagerness to solve complex problems in novel ways.
- Designs AI infrastructure that’s production-ready, not just experimental.
- Automates LLM workflows using scripting and orchestration frameworks.
- Balances innovation with maintainability in a fast-scaling environment.
- Identifies opportunities to embed AI into core business operations.
- Bridges technical depth with clear communication and business alignment.
- Salary Range: Competitive Pay
- Bi-annual Salary Review (eligibility condition applies).
- Festival bonus (eligibility condition applies).
- Celebrate with birthday leaves and great team events.
- Unwind together at annual company retreats.
- Kick back with game nights and all-access sports zones – billiards, foosball, PlayStation, cricket, football & badminton.
- Get moving with an in-house fitness trainer to keep your mind and body in sync.
- Start the next chapter in your life, with our special honeymoon package.
- Opportunities for relocation to Sri Lanka and Malaysia, subject to business needs, with travel allowances.
- 30 minute HR interview with the Talent Acquisition team member
- 45 minute Problem Solving Interview session
- 60-minute Bar Raiser Interview session
At NEXT Ventures, we believe the right talent fuels breakthrough innovation. If you're driven to connect great minds with big ideas and want to shape the future of fintech, we’d love to meet you. Join our team of bold thinkers where technology meets transformation.
Apply now and be part of our journey — the future is calling, and it starts with you.