The job responsibilities outlined in this document are not exhaustive and may evolve over time and be reviewed according to business needs.
Role Description Summary
We are seeking a Senior Applied AI & Data Science Engineer to design, build, and deploy AI-powered solutions that transform how our organization works with data. This role will focus on developing AI agents, automating business workflows, enabling natural language access to enterprise data, and applying machine learning and advanced analytics to solve complex business problems. The ideal candidate combines strong data science and machine learning expertise with practical software engineering skills and hands-on experience building AI applications in production environments.
Primary Responsibilities / Key Result Areas
Design, develop, and deploy AI agents and AI-powered applications for internal business stakeholders.
Build solutions using LLMs, Retrieval-Augmented Generation (RAG), and agent-based architectures.
Develop machine learning models for prediction, classification, anomaly detection, forecasting, and optimization use cases.
Create natural language interfaces for enterprise data and analytics platforms.
Integrate AI applications with enterprise systems through APIs and cloud-native services.
Build scalable data pipelines and analytics solutions using large datasets.
Partner with business stakeholders to identify and deliver high-impact AI and data science opportunities.
COMPETENCIES
Desire and ability to work in a highly collaborative environment which includes working on cross-functional teams and demonstrating the flexibility to assume lead or support roles.
Strong analytical and problem-solving skills. Ability to take lead and manage work in an efficient manner.
Effective interpersonal skills and well-developed communication skills (oral, written, listening).
Effectively able to manage competing priorities and handle multiple projects independently.
Ability to make strategic recommendations.
Ability to present technical information to a non-technical audience.
Qualifications & Experience
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field.
3-5 years of experience in Data Science, Machine Learning, Analytics Engineering, or Software Engineering.
Strong programming skills in Python and advanced SQL.
Expert knowledge of multiple machine learning algorithms/techniques such as clustering, neural network, random forest, time series analysis, and XGBoost.
Experience building applications using modern LLMs and Generative AI technologies.
Proficiency with AWS, Azure, or Snowflake cloud computing platforms.
Capability with Tableau, Power BI, or other business intelligence tools.
Strong understanding of statistics, machine learning, and data modeling.
Excellent problem-solving, communication, and stakeholder management skills.
Other Key Requirements / Comments
Bachlors in computer science, Engineering, or Information Systems
Proficiency with Amazon Bedrock, Anthropic Claude, Azure OpenAI, OpenAI, or similar AI platforms.
Knowledge of AI frameworks such as Agentic AI, CrewAI, LangChain, LangGraph, MCP, RAG, and vector databases.
Familiarity with MLOps responsibilities: model deployment, monitoring, and governance practices.
Experience in airline / aviation, internet, or telecommunications
SES and its Affiliated Companies are committed to providing fair and equal employment opportunities to all. We are an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, gender, pregnancy, sex, sexual orientation, gender identity, national origin, age, genetic information, protected veteran status, disability, or any other basis protected by local, state, or federal law.
Telecommunications Defense And Space Manufacturing And IT Services And IT Consulting
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