Senior AI Engineer
Job Description
Company Description SoftNice is an award-winning global technology company that helps enterprises drive digital transformation through modern IT solutions and services. The organization delivers innovative software across areas such as cloud, security, data and business intelligence, mobility, collaboration platforms, and custom .NET applications to improve productivity and business outcomes. In addition to technology solutions, SoftNice has over 22 years of experience in IT staffing, serving Fortune 500 and large enterprises with flexible talent models including contract, contract-to-hire, and permanent placements. With headquarters in Allentown, PA and development centers in India, the company combines the reliability of a U.S. corporation with the advantages of cost-effective offshore development. Since 2001, SoftNice has supported customers across multiple industries, enabling them to optimize their technology investments and achieve meaningful digital innovation.
Role Description The Senior AI Engineer contract role is a remote position focused on designing, developing, and deploying AI-driven solutions that support SoftNice's enterprise clients. Day-to-day responsibilities include building and optimizing machine learning models, implementing pattern recognition and neural network architectures, and applying NLP techniques to real-world business problems. The engineer will collaborate with cross-functional teams to gather requirements, integrate AI components into existing software systems, and ensure solutions are scalable, secure, and maintainable. This role also involves conducting experiments, evaluating model performance, documenting technical designs, and providing guidance on AI best practices to stakeholders and junior engineers.
Qualifications
Role Description The Senior AI Engineer contract role is a remote position focused on designing, developing, and deploying AI-driven solutions that support SoftNice's enterprise clients. Day-to-day responsibilities include building and optimizing machine learning models, implementing pattern recognition and neural network architectures, and applying NLP techniques to real-world business problems. The engineer will collaborate with cross-functional teams to gather requirements, integrate AI components into existing software systems, and ensure solutions are scalable, secure, and maintainable. This role also involves conducting experiments, evaluating model performance, documenting technical designs, and providing guidance on AI best practices to stakeholders and junior engineers.
Qualifications
- Strong foundation in Computer Science and Software Development, including data structures, algorithms, and scalable system design.
- Hands-on experience with Neural Networks and Pattern Recognition, using modern machine learning frameworks and tools.
- Proficiency in Natural Language Processing (NLP), including model training, fine-tuning, and deployment for production use cases.
- Advanced programming skills in languages such as Python, Java, or C++, and familiarity with cloud platforms (e.g., Azure, AWS, or GCP).
- Experience building end-to-end AI solutions, from data preparation and model experimentation to monitoring and continuous improvement.
- Ability to work effectively in remote, distributed teams, with strong communication and documentation skills.
- Bachelor's or Master's degree in Computer Science, Data Science, or a related technical field, or equivalent practical experience.
- Background in enterprise environments or consulting and familiarity with MLOps practices is highly beneficial.
More Info
About Company
Skills:
C++, Python, Data pipelines and model pipelines, Deployment observability and production readiness, GenAI LLM application development, Scalable system design, ML training and evaluation workflows
Skills:
Sql, Tensorflow, Numpy, Git, Pandas, Pytorch, Databricks, Rest Apis, Python, Scikit-learn, ADLS Gen2, MLflow, Delta Live Tables, Azure Data Lake Storage, Delta Lake, AI ML libraries
Skills:
data engineering , Machine Learning, MLops, Computer Vision, Natural Language Processing, Software Engineering, Azure, Cloud Technologies, Google Cloud, AWS, data preprocessing
Skills:
Python, Testing, LangGraph or equivalent agentic orchestration frameworks, observability, tracing, CI/CD, Claude Anthropic API and Claude Code, MCP-based interoperability patterns and tool-calling agent design, and debugging for LLM-based systems, Multi-agent orchestration and agent collaboration patterns
Skills:
prophet , API design, Indexes, XGBoost, Predictive Modelling, Pandas, Machine Learning, Systems Integration, embeddings, LLM application engineering, Python ML stack, scikit-learn, assistant custom-GPT development, model training, supervised learning, vector databases, Git-based collaborative development, RAG at production quality, tuning and evaluation, context management for large document sets, tool function calling, Strong Python engineering, time-series forecasting, retrieval tuning, statsmodels, prompt design, evaluation and guardrails