Trident ConsultingRemote
Senior Full Stack Java Engineer
United States of America
Contract
1 day ago
$60 USD
No H1B
Key skills
GitHub Spec KitSpec-driven developmentReactJavaScriptTypeScriptNext.jsVueNode.jsREST APIsGraphQL APIsAWS LambdaAWS S3AWS EC2AWS API GatewayAWS RDSAWS CloudFormationMongoDBPostgreSQLAI agent frameworksLLM APIsOpenAI APIAnthropic APIPrompt engineeringData structuresSystem designTestingCI/CD practicesSupervised learningLinear regressionLogistic regressionDecision treesRandom ForestGradient BoostingXGBoostLightGBMCatBoostSupport Vector MachinesKernel methodsNeural networksCNNsRNNsLSTMsTransformersClassificationRegressionRanking problemsCross-validationBias-variance trade-offRegularizationL1 regularizationL2 regularizationDropoutUnsupervised learningK-Means clusteringDBSCANGaussian Mixture ModelsHierarchical clusteringPCAt-SNEUMAPAutoencodersVariational autoencodersAnomaly detectionOutlier identificationAssociation rule miningAprioriFP-GrowthTopic modellingLDANMFReinforcement learningMarkov Decision ProcessesQ-LearningSARSADeep Q-NetworksPolicy gradient methodsREINFORCEPPOA3CA2CActor-Critic architecturesMulti-armed banditsContextual banditsReward shapingSimulation frameworksOpenAI GymTransfer learningFine-tuning pre-trained modelsSemi-supervised learningSelf-supervised learningActive learningHuman-in-the-loop pipelinesFederated learningBayesian optimizationHyperparameter tuningOptunaRay TuneEnsemble methodsStackingModel blendingGraph Neural NetworksCausal inferenceCounterfactual reasoningJavaAIMLGenAILLMOpenAIAnthropicGraphQLAWSCloudFormationEC2LambdaS3RDSAPI GatewayRESTfulGitHubCI/CD
About this role
Trident Consulting is an award-winning staffing and consulting firm seeking a Senior Full Stack Java Engineer for one of their clients, a global leader in business and technology services. The role involves leading development initiatives, designing and building web applications, and deploying cloud-native solutions while collaborating with various teams to enhance product capabilities.
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 Node.js, 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
Requirements:
- 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 (Next.js, Vue, or similar)
- Solid backend development skills with Node.js — 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
- Bachelor's degree in computer science, Engineering, or equivalent practical experience
- Supervised Learning: Linear regression and logistic regression, Decision trees, Random Forest, Gradient Boosting (XGBoost, LightGBM, CatBoost), Support Vector Machines (SVMs) and kernel methods, Neural networks — CNNs, RNNs, LSTMs, and Transformers, Classification, regression, and ranking problems, Cross-validation, bias-variance trade-off, regularization (L1/L2, dropout)
- Unsupervised Learning: Clustering: K-Means, DBSCAN, Gaussian Mixture Models, hierarchical clustering, Dimensionality reduction: PCA, t-SNE, UMAP, Autoencoders and variational autoencoders (VAEs), Anomaly detection and outlier identification, Association rule mining (Apriori, FP-Growth), Topic modelling (LDA, NMF)
- Reinforcement Learning: Markov Decision Processes (MDPs) states, actions, rewards, transitions, Model-free methods: Q-Learning, SARSA, Deep Q-Networks (DQN), Policy gradient methods: REINFORCE, PPO, A3C / A2C, Actor-Critic architectures, Multi-armed bandits and contextual bandits, Reward shaping, environment design, and simulation frameworks (OpenAI Gym)
- Relevant learning algorithms - Adjacent & advanced techniques: Transfer learning and fine-tuning pre-trained models, Semi-supervised and self-supervised learning, Active learning and human-in-the-loop pipelines, Federated learning for privacy-preserving training, Bayesian optimization and hyperparameter tuning (Optuna, Ray Tune), Ensemble methods, stacking, and model blending, Graph Neural Networks (GNNs) a plus, Causal inference and counterfactual reasoning — a plus