Sr. AI Engineer
Job Location:
Job Location:
Atlanta, GA - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
7 hours ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Role:FSE Engineer
Atlanta GA
Hybrid or Remote is acceptable.
Top 3 skills required for this role:
1. Hands-on experience with GitHub Spec Kit and spec-driven development using AI agents (/specify /plan /tasks workflow).
2. Production-grade applications built with React / JavaScript frameworks and REST/GraphQL APIs.
3. AWS infrastructure (Lambda S3 EC2 API Gateway) paired with MongoDB and/or PostgreSQL at scale.
Job Description/ Responsibilities
Lead spec-first development initiatives using GitHub Spec Kit - authoring specs technical plans and agent-ready task breakdowns before writing any code.
Design and build full stack web applications using React JavaScript/TypeScript frameworks and from UI to backend API layer.
Develop integrate and maintain RESTful and GraphQL APIs ensuring performance reliability and security across services.
Architect and deploy cloud-native solutions on AWS (Lambda EC2 S3 API Gateway RDS CloudFormation) with a focus on scalability and cost efficiency.
Build and integrate AI-powered features - leveraging LLMs AI agents prompt engineering and the GenAI ecosystem to enhance product capabilities.
Design and manage relational (PostgreSQL) and document (MongoDB) databases including schema design query optimisation and data migrations.
Collaborate with product managers designers and AI/ML engineers to translate requirements into well-specified shippable software.
Participate in code reviews establish engineering best practices and contribute to a culture of quality and continuous improvement.
Required Qualifications
5 years of professional experience in full stack software development.
Proven hands-on experience with GenAI tools and a spec-first development approach including GitHub Spec Kit or equivalent workflows.
Strong proficiency in React and modern JavaScript / TypeScript frameworks ( Vue or similar).
Solid backend development skills with - building and maintaining production REST or GraphQL APIs.
Experience deploying and operating applications on AWS - comfortable with core services such as Lambda EC2 S3 API Gateway and RDS.
Practical experience with both MongoDB (document store) and PostgreSQL (relational) including schema design and query tuning.
Familiarity with AI agent frameworks LLM APIs (OpenAI Anthropic or similar) and prompt engineering techniques.
Strong understanding of software engineering fundamentals - data structures system design testing and CI/CD practices.
Bachelors degree in computer science Engineering or equivalent practical experience.
Required Technical Expertise
Supervised Learning
o Linear regression and logistic regression
o Decision trees Random Forest Gradient Boosting (XGBoost LightGBM CatBoost)
o Support Vector Machines (SVMs) and kernel methods
o Neural networks - CNNs RNNs LSTMs and Transformers
o Classification regression and ranking problems
o Cross-validation bias-variance trade-off regularization (L1/L2 dropout)
Unsupervised Learning
o Clustering: K-Means DBSCAN Gaussian Mixture Models hierarchical clustering
o Dimensionality reduction: PCA t-SNE UMAP
o Autoencoders and variational autoencoders (VAEs)
o Anomaly detection and outlier identification
o Association rule mining (Apriori FP-Growth)
o Topic modelling (LDA NMF)
Reinforcement Learning
o Markov Decision Processes (MDPs) states actions rewards transitions
o Model-free methods: Q-Learning SARSA Deep Q-Networks (DQN)
o Policy gradient methods: REINFORCE PPO A3C / A2C
o Actor-Critic architectures
o Multi-armed bandits and contextual bandits
o Reward shaping environment design and simulation frameworks (OpenAI Gym)
Relevant learning algorithms - Adjacent & advanced techniques
o Transfer learning and fine-tuning pre-trained models
o Semi-supervised and self-supervised learning
o Active learning and human-in-the-loop pipelines
o Federated learning for privacy-preserving training
o Bayesian optimization and hyperparameter tuning (Optuna Ray Tune)
o Ensemble methods stacking and model blending
o Graph Neural Networks (GNNs) a plus
o Causal inference and counterfactual reasoning - a plus
Good to Have
Experience with GitHub Copilot Cursor or other AI-assisted coding environments in day-to-day development.
Familiarity with containerization (Docker Kubernetes) and infrastructure-as-code (Terraform AWS CDK).
Exposure to vector databases (Pinecone pgvector) or RAG (Retrieval-Augmented Generation) pipelines.
Knowledge of event-driven architectures using AWS SQS SNS or Event Bridge.
Experience with LangChain LlamaIndex or similar AI orchestration frameworks.
Contributions to open-source projects or a portfolio of AI-integrated applications.
Familiarity with observability tools - Data Dog CloudWatch or Splunk - for monitoring AI and API workloads.
About Company
Previous Next We Are Hiring! Search Staffing & Managed Services Recruitment Branding Solutions Product Engineering Solutions Why Reqroute? Our Market niche is towards Social Media Recruiting and we effectively use social media platforms to reach out to a pool of active/passive candida ... View more
