What are the responsibilities and job description for the AI Engineer (Financial Services) position at First Soft Solutions LLC?
AI Engineer (Enterprise AI Platforms)
Location: [Onsite / Hybrid / Remote]
Employment Type: Full-Time (W2 Only)
No Corp-to-Corp (C2C)
About The Role
We are seeking an AI Engineer to design, develop, and deploy enterprise AI solutions within a financial services environment. This role focuses on building production-grade AI systems using machine learning, large language models (LLMs), and data-driven architectures to support use cases such as risk analysis, fraud detection, customer intelligence, and regulatory automation.
You will work in a highly regulated environment, ensuring all AI solutions are secure, explainable, and compliant with financial standards.
Key Responsibilities
Location: [Onsite / Hybrid / Remote]
Employment Type: Full-Time (W2 Only)
No Corp-to-Corp (C2C)
About The Role
We are seeking an AI Engineer to design, develop, and deploy enterprise AI solutions within a financial services environment. This role focuses on building production-grade AI systems using machine learning, large language models (LLMs), and data-driven architectures to support use cases such as risk analysis, fraud detection, customer intelligence, and regulatory automation.
You will work in a highly regulated environment, ensuring all AI solutions are secure, explainable, and compliant with financial standards.
Key Responsibilities
- Design and develop AI/ML models and LLM-based applications for enterprise use cases
- Build and deploy RAG (Retrieval-Augmented Generation) pipelines and intelligent systems
- Develop scalable data pipelines and AI workflows
- Integrate AI solutions with enterprise systems, APIs, and data platforms
- Implement model monitoring, evaluation, and optimization
- Ensure explainability, auditability, and compliance of AI systems
- Work with large structured and unstructured datasets
- Collaborate with cross-functional teams to deliver AI-driven solutions
- Support deployment using cloud platforms and MLOps practices
- 4 years of experience in AI/ML engineering or data science
- Strong programming skills in Python
- Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn)
- Experience building LLM-based applications and RAG pipelines
- Strong understanding of data processing, feature engineering, and model evaluation
- Experience with APIs, microservices, and system integration
- Experience working in enterprise environments (financial preferred)
- Experience with LLMs (GPT, Claude, Llama, Mistral)
- Familiarity with vector databases (Pinecone, FAISS, Weaviate)
- Experience with MLOps tools and model deployment
- Experience with cloud platforms (AWS, Azure, GCP)
- Knowledge of data security, governance, and compliance requirements
- Exposure to financial use cases (fraud detection, risk, compliance)
- Strong AI/ML engineering and problem-solving skills
- Ability to build scalable, production-ready AI systems
- Understanding of model explainability and regulatory requirements
- Experience delivering enterprise AI solutions in real-world environments