Website:
welsbach.group
Job details:
About Welsbach
Welsbach was founded in 2021 with a singular vision: to become Asia's leading bridge between high-growth companies and global capital markets.
Our team of seasoned investment banking professionals, with decades of combined experience at tier-one institutions including Goldman Sachs, JP Morgan, Deutsche Bank, and Macquarie, recognized the critical opportunity in cross-border SPAC and IPO transactions across Asia–West corridors.
Today, we operate at the intersection of capital markets, technology, and advisory, supporting complex cross-border transactions and strategic mandates with deep institutional expertise and global connectivity.
As we scale, we are investing in building world-class internal technology platforms and AI-driven systems that power our advisory workflows, research, analytics, and execution capabilities.
Role OverviewWelsbach is seeking a highly capable Full Stack Developer with strong AI Systems Development capability to design, build, and scale production-grade internal systems used by senior investment professionals.
This is a high-ownership role at the intersection of finance, software engineering, and artificial intelligence. You will work directly with leadership, bankers, and analysts to translate complex real-world transaction workflows into scalable, secure, and intelligent technology solutions.
Key Responsibilities
Application Development & Architecture
- Design, develop, and maintain end-to-end web applications across frontend and backend
- Build scalable, secure, high-performance systems used across research, analytics, and internal operations
- Own architectural decisions with a focus on long-term maintainability and performance
- Manage deployments, monitoring, and continuous improvement of production systems
AI & Data Systems Development
- YMulti-step AI agents that autonomously conduct research, synthesize data, and produce structured outputs across deal workflows
- Agentic pipelines using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, or custom agent architectures
- Tool-use and function-calling systems that connect LLMs to live data sources, APIs, and internal databases
- Memory architectures — short-term, long-term, episodic — using vector databases (Pinecone, Weaviate, pgvector) and retrieval-augmented generation (RAG)
- Evaluation and observability frameworks to monitor agent reliability, output quality, and hallucination rates in production
- Structured output systems for document analysis, extraction, and classification across unstructured capital markets data
LLM Integration & Model Engineering
- Work hands-on with both frontier models (OpenAI, Anthropic, Gemini) and open-source LLMs (Llama 3, Mistral, Qwen, DeepSeek, Phi)
- Fine-tune, quantize, and deploy open-source models using tools such as Hugging Face Transformers, Unsloth, vLLM, and Ollama
- Engineer advanced prompting strategies chain-of-thought, few-shot, self-consistency, reflection and systematic prompt evaluation pipelines
- Build and maintain embeddings pipelines and semantic search systems for retrieval over large document corpora
- Contribute to or draw from open-source LLM tooling; familiarity with the OSS AI ecosystem is a strong plus
Collaboration & Business Integration
- Work closely with senior leadership and investment banking teams to understand transaction workflows
- Translate complex advisory problems into clear technical architectures
- Partner across functions to deliver solutions from concept to deployment
- Provide structured input on feasibility, timelines, and system trade-offs
Platform Reliability & Security
- Ensure high standards of performance, security, and data privacy
- Implement appropriate access controls, auditability, and best practices for financial services environments
- Proactively identify technical risks and system bottlenecks
Required QualificationsEducation
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
- Strong foundation in software engineering and data systems
Professional Experience
- 3+ years building and maintaining production-grade full stack applications
- 2+ years of hands-on experience building production AI agents or LLM-powered systems
- Demonstrated experience deploying and scaling live systems
- Proven experience integrating AI/ML capabilities into real products (not only prototypes)
Technical Skills
Full Stack
- Strong proficiency in JavaScript / TypeScript
- Frontend frameworks: React, Next.js, or equivalent
- Backend development using Node.js, Python, or similar
- API design (REST / GraphQL)
- Databases: PostgreSQL, MySQL, MongoDB, or equivalent
Cloud & Infrastructure
- Experience deploying on AWS, GCP, or Azure
- Familiarity with CI/CD, monitoring, logging, and system reliability
AI & Data
- Hands-on experience with LLMs
- Understanding of prompt engineering, embeddings, and vector databases
- Experience with Python data tools (Pandas, NumPy)
- Ability to embed AI capabilities into real business workflows
What We OfferCareer & Exposure
- Direct exposure to senior professionals from top-tier global investment banks
- Opportunity to build technology used in real capital market transactions
- High ownership over core internal platforms
- The ability to shape how AI is applied within a serious financial institution
Compensation
- Competitive compensation aligned with experience and impact
- Performance-linked growth as internal platforms scale
Click on Apply to know more.