WHO YOU ARE:

Senior Software engineer plays a key role in the design, development/configuration, unit testing, installation, and ongoing maintenance of Zinnia software platforms. Works with stakeholders to develop solutions and/or products that fulfill the needs of Zinnia’s internal stakeholders and clients. Those solutions and/or products help Zinnia and Zinnia clients to be more efficient and provide better service to end customers. Technical Architect interacts directly with project managers and business stakeholders and may periodically interact directly with Zinnia’s clients. Will facilitate, Architect, and enable junior team members by acting as a mentor for soft skills and/or technical subject matter experts.

WHAT YOU’LL DO:

• Work as part of a global, cross-functional team to develop innovative software for Zinnia’s stakeholders.
• Contribute to projects by creating well-designed, customized, testable, and efficient code for Life & Annuity Exchange
• Assist our teams in providing ongoing support, troubleshooting, improvements, or custom enhancements to existing Life & Annuity Exchange
• Flexibility to support the challenging development and delivery needs of Zinnia
• Collaborate with our global teams, internal stakeholders, and customers.
• Act as a mentor and technology expert for team members and conduct technical reviews.
• Architect, Design, develop and validate various requirements for the Zinnia platforms
• Ability to work in a fast-paced environment, recognize and react to changing business needs and effectively prioritize tasks
• Must be self-motivated and able to work independently and in conjunction with team members and business units. Enthusiasm and flexibility to work on a variety of projects

WHAT YOU’LL NEED:

• 10+ years of expertise across the full Microsoft .NET ecosystem — owning technical direction from architecture design through production, setting standards, mentoring engineers, and driving SDLC maturity within Agile/Scrum organizations; deep expertise in C#, ASP.NET Core, and enterprise design patterns
• Architecting, designing, developing, and delivering solutions using C#/.NET, ASP.NET Core, MVC, Web API, Visual Studio IDE, SSRS, SOAP, XML, GitHub; leads API design strategy at scale — defining standards for security (OAuth2, JWT), versioning, documentation (OpenAPI/Swagger), and performance across distributed microservices environments
• Understanding of advanced design patterns, API-first design, and SOLID principles
• Effective communication, interpersonal, and critical thinking skills.
• Effective troubleshooting skills.
• Ability to work as part of a cross-functional, global team.
• Fluent client communication, Issue management, deployment, and delivery support;
• Hands-on experience designing and deploying cloud solutions on AWS — working across compute, storage, and serverless services with a focus on scalability and cost efficiency; contributes to cloud best practices and supports team adoption
• Team coordination, analytical skill, self-learning, Communication, Technical documentation, system analysis
• Contributes to RESTful API design strategy at scale, helping define standards for security (OAuth2, JWT), versioning, documentation (OpenAPI/Swagger), and performance. Supports the design of integration layers between systems and promotes API governance across distributed teams and microservices environments
• Exposure to AI integration, including LLM APIs, prompt engineering, RAG pipelines, and AI-powered feature development, with a willingness to apply emerging AI capabilities to real-world product use cases

Good to have:

• Working experience on enterprise-level applications/products
• Working experience in React/Angular
• Insurance/financial services (Life and Annuity) industry knowledge
• Experience with Web-based software as a service (SaaS) application
• Knowledge of Redis Cache for in-memory data structure storage and caching
  
  

WHAT’S IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability

BOLD is seeking for newest addition to our existing Data Science team, you’ll combine your analytical skills and business knowledge to deliver key insights to our Product and Management teams. You’ll help drive product development using our vast user data sets to enhance our current products and to help us find inferences and relationships in this data to build new products – More towards the role required

ABOUT THIS TEAM

The Data Science department at BOLD is responsible for discovering patterns and trends in datasets to get insights, creating predictive algorithms and data models, improving the quality of data or product offerings by utilizing machine learning techniques, distributing suggestions to other teams and top management, and using data tools such as Python and SQL.

The Data Science team actively collaborates with other vertical teams such as Engineering, Portals, BI, Product, Legal. Most of the projects are focused around problems that require a mix of natural language processing and machine learning. Some of the active projects are resume parsing, ranking, summary generation, data quality and scoring, content generation, job recommendations, and conversion analysis. Apart from the business initiatives, the team also explores state of the art methods and keeps them upto to date with technology.

WHAT YOU’LL DO 

• Demonstrate ability to work on data science projects involving predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc. 
• Leverage our rich data sets of user data to perform research, develop models and create data products with our Development & Product teams 
• Develop novel and scalable data systems in cooperation with our system architects that leverage datasets using machine learning techniques to enhance the user experience 

WHAT YOU’LL NEED 

• Knowledge and experience using statistical and machine learning algorithms including regression, instance-based learning, decision trees, Bayesian statistics, clustering, neural networks, deep learning, ensemble methods 
• Expert knowledge in Python.  
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Should have done one or more projects involving fine-tuning with LLMs 
• Experience in feature selection, building and optimising classifiers. 
• Experience working with backend technologies such as Flask/ Gunicorn etc. 
• Experience on working with open source library such Spacy,NLTK,Gensim etc  
• Experience on working with deep-learning library such as Tensor flow, Pytorch etc  
• Experience with software stack components including common programming languages, back-end technologies, database modelling, continuous integration, services oriented architecture, software testability etc. 
• Be a keen learner and enthusiastic about developing software.    

EXPERIENCE- 

• Software Engineer- 2.5 years+
• Senior Software Engineer-4.5 years+

#LI-SV1

Senior Machine Learning Engineer

Location: (Bangalore or Noida) 

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data

As a Machine Learning Engineer, you’ll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.

You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.

Responsibilities

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

Required Qualifications

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 4-6 years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Strong communication skills and a passion for shaping emerging AI paradigms.

Desired Qualifications

• Prior experience building and deploying AI agents or LLM applications in production.
• Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.

About Us

Sumo Logic, Inc. helps make the digital world secure, fast, and reliable by unifying critical security and operational data through its Intelligent Operations Platform. Built to address the increasing complexity of modern cybersecurity and cloud operations challenges, we empower digital teams to move from reaction to readiness—combining agentic AI-powered SIEM and log analytics into a single platform to detect, investigate, and resolve modern challenges. Customers around the world rely on Sumo Logic for trusted insights to protect against security threats, ensure reliability, and gain powerful insights into their digital environments. For more information, visit www.sumologic.com.

Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

WHO YOU ARE:

Software Engineer plays a key role in the design, development/configuration, unit testing, installation, and ongoing maintenance of Zinnia software platforms. Works with stakeholders to develop solutions and/or products that fulfill the needs of Zinnia’s internal stakeholders and clients. Those solutions and/or products help Zinnia and Zinnia clients to be more efficient and provide better service to end customers. Software Engineer interacts directly with project managers and business stakeholders and may periodically interact directly with Zinnia’s clients. Will facilitate, Architect, and enable junior team members by acting as a mentor for soft skills and/or technical subject matter experts.

WHAT YOU’LL DO:

• Work as part of a global, cross-functional team to develop innovative software for Zinnia’s stakeholders.
• Contribute to projects by creating well-designed, customized, testable, and efficient code for Life & Annuity Exchange
• Assist our teams in providing ongoing support, troubleshooting, improvements, or custom enhancements to existing Life & Annuity Exchange
• Flexibility to support the challenging development and delivery needs of Zinnia
• Collaborate with our global teams, internal stakeholders, and customers.
• Ability to work in a fast-paced environment, recognize and react to changing business needs and effectively prioritize tasks
• Must be self-motivated and able to work independently and in conjunction with team members and business units. Enthusiasm and flexibility to work on a variety of projects

WHAT YOU’LL NEED:

• Microsoft .NET (5–7 Years) Deep, well-rounded expertise across the complete software development lifecycle using .NET technologies. Consistently delivers end-to-end solutions — from requirements gathering through production deployment — within Agile/Scrum teams. Core stack: C#, ASP.NET Core, MVC, and Web API, utilizing Visual Studio IDE, SSRS, SOAP, XML, and GitHub. Strong understanding of advanced design patterns, API-first design, and SOLID principles.
• AWS (Cloud) Hands-on experience deploying and managing cloud infrastructure on AWS — covering compute, storage, serverless, and observability. Able to work independently across the cloud stack, moving beyond basic service consumption to support real engineering needs.
• RESTful API Skilled in designing, building, and consuming secure RESTful APIs with a strong command of industry standards. Well-versed in OAuth2 authentication, OpenAPI/Swagger documentation, and API testing workflows using Postman.
• AI Integration Practical, hands-on experience embedding AI capabilities into production software — including LLM API integration, prompt engineering, and developing AI-adjacent features. Actively deepening this expertise as a core part of a modern engineering toolkit.
• Collaboration & Communication Effective communicator with strong interpersonal and critical thinking skills. Experienced working within cross-functional, global teams — handling client communication, issue management, deployment support, and technical documentation with confidence.

Good to have:

• Working experience on enterprise-level applications/products
• Working experience in React/Angular, REACT, KONG, JIRA
• Experience with Web-based software as a service (SaaS) application
• Knowledge of Redis Cache for in-memory data structure storage and caching

WHAT’S IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

#LI-AS2

WHO YOU ARE

You are a passionate Python and AI/ML Engineer minimum 4 years of hands-on experience building intelligent systems. You thrive in fast-paced environments, love solving complex problems with data and algorithms, and take pride in delivering AI solutions that create real business impact. You have experience with cutting-edge Generative AI, scalable ML pipelines, and production-grade systems and you're energized by working at the frontier of what AI can do.

WHAT YOU'LL DO

1. Design, develop, and deploy machine learning models and Generative AI solutions — including classification, clustering, summarization, search & ranking, and information extraction.
2. Own end-to-end ML pipelines — from data ingestion and preprocessing through model training, deployment, and production monitoring.
3. Collaborate with cross-functional teams to translate business requirements into AI-driven features — applying NLP, outlier detection, and deep learning techniques where applicable.
4. Build robust, scalable, and well-documented Python-based RESTful APIs to expose ML models and AI services in production environments.
5. Optimize database interactions and ensure efficient data storage and retrieval for AI applications across SQL and NoSQL systems.
6. Stay current with the latest advances in AI/ML — integrating emerging approaches such as RAG pipelines, LLM fine-tuning, and vector search into live products.

WHAT YOU'LL NEED 

Python
Strong hands-on proficiency for building, scripting, and deploying AI/ML systems.
NumPy · Pandas · FastAPI · Scikit-learn
Machine Learning
Applied expertise across supervised, unsupervised, and deep learning — classification, clustering, outlier detection.
PyTorch · TensorFlow · XGBoost · DBSCAN

Generative AI (2+ yrs)
Hands-on experience building with LLMs — prompt engineering, RAG pipelines, summarization, and AI-powered features.
LLMs · RAG · Prompt Eng. · Fine-tuning

NLP & Search / Ranking
Processes language and builds relevance engines — NER, embeddings, semantic search, and ranking models.
spaCy · BERT · FAISS · Elasticsearch

API Development
Designs and ships secure, well-documented RESTful APIs exposing ML models as production-ready services.
REST · FastAPI · OAuth2 · Swagger

Databases
Proficient in SQL and NoSQL stores for structured and unstructured data pipelines supporting AI workloads.
PostgreSQL · MongoDB · Vector DBs

GOOD TO HAVE

Cloud Platforms
Deploys and scales AI workloads on AWS, Azure, or GCP.
AWS · Azure

TypeScript / JavaScript
Frontend or full-stack exposure for building ML-powered product interfaces.
TypeScript · React · Node.js

MLOps
Manages the ML lifecycle — tracking, versioning, and pipeline automation.
MLflow · Kubeflow · CI/CD

Containerization & Orchestration
Packages and scales AI services using containers and cluster management.
Docker · Kubernetes

WHO YOU ARE:

Senior Software engineer plays a key role in the design, development/configuration, unit testing, installation, and ongoing maintenance of Zinnia software platforms. Works with stakeholders to develop solutions and/or products that fulfill the needs of Zinnia’s internal stakeholders and clients. Those solutions and/or products help Zinnia and Zinnia clients to be more efficient and provide better service to end customers. Technical Architect interacts directly with project managers and business stakeholders and may periodically interact directly with Zinnia’s clients. Will facilitate, Architect, and enable junior team members by acting as a mentor for soft skills and/or technical subject matter experts.

WHAT YOU’LL DO:

• Work as part of a global, cross-functional team to develop innovative software for Zinnia’s stakeholders.
• Contribute to projects by creating well-designed, customized, testable, and efficient code for Life & Annuity Exchange
• Assist our teams in providing ongoing support, troubleshooting, improvements, or custom enhancements to existing Life & Annuity Exchange
• Flexibility to support the challenging development and delivery needs of Zinnia
• Collaborate with our global teams, internal stakeholders, and customers.
• Act as a mentor and technology expert for team members and conduct technical reviews.
• Architect, Design, develop and validate various requirements for the Zinnia platforms
• Ability to work in a fast-paced environment, recognize and react to changing business needs and effectively prioritize tasks
• Must be self-motivated and able to work independently and in conjunction with team members and business units. Enthusiasm and flexibility to work on a variety of projects

WHAT YOU’LL NEED:

• 10+ years of expertise across the full Microsoft .NET ecosystem — owning technical direction from architecture design through production, setting standards, mentoring engineers, and driving SDLC maturity within Agile/Scrum organizations; deep expertise in C#, ASP.NET Core, and enterprise design patterns
• Architecting, designing, developing, and delivering solutions using C#/.NET, ASP.NET Core, MVC, Web API, Visual Studio IDE, SSRS, SOAP, XML, GitHub; leads API design strategy at scale — defining standards for security (OAuth2, JWT), versioning, documentation (OpenAPI/Swagger), and performance across distributed microservices environments
• Understanding of advanced design patterns, API-first design, and SOLID principles
• Effective communication, interpersonal, and critical thinking skills.
• Effective troubleshooting skills.
• Ability to work as part of a cross-functional, global team.
• Fluent client communication, Issue management, deployment, and delivery support;
• Hands-on experience designing and deploying cloud solutions on AWS — working across compute, storage, and serverless services with a focus on scalability and cost efficiency; contributes to cloud best practices and supports team adoption
• Team coordination, analytical skill, self-learning, Communication, Technical documentation, system analysis
• Contributes to RESTful API design strategy at scale, helping define standards for security (OAuth2, JWT), versioning, documentation (OpenAPI/Swagger), and performance. Supports the design of integration layers between systems and promotes API governance across distributed teams and microservices environments
• Exposure to AI integration, including LLM APIs, prompt engineering, RAG pipelines, and AI-powered feature development, with a willingness to apply emerging AI capabilities to real-world product use cases

Good to have:

• Working experience on enterprise-level applications/products
• Working experience in React/Angular
• Insurance/financial services (Life and Annuity) industry knowledge
• Experience with Web-based software as a service (SaaS) application
• Knowledge of Redis Cache for in-memory data structure storage and caching
  
  

WHAT’S IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability

#LI-AS2

WHO YOU ARE:

Software Engineer plays a key role in the design, development/configuration, unit testing, installation, and ongoing maintenance of Zinnia software platforms. Works with stakeholders to develop solutions and/or products that fulfill the needs of Zinnia’s internal stakeholders and clients. Those solutions and/or products help Zinnia and Zinnia clients to be more efficient and provide better service to end customers. Software Engineer interacts directly with project managers and business stakeholders and may periodically interact directly with Zinnia’s clients. Will facilitate, Architect, and enable junior team members by acting as a mentor for soft skills and/or technical subject matter experts.

WHAT YOU’LL DO:

• Work as part of a global, cross-functional team to develop innovative software for Zinnia’s stakeholders.
• Contribute to projects by creating well-designed, customized, testable, and efficient code for Life & Annuity Exchange
• Assist our teams in providing ongoing support, troubleshooting, improvements, or custom enhancements to existing Life & Annuity Exchange
• Flexibility to support the challenging development and delivery needs of Zinnia
• Collaborate with our global teams, internal stakeholders, and customers.
• Ability to work in a fast-paced environment, recognize and react to changing business needs and effectively prioritize tasks
• Must be self-motivated and able to work independently and in conjunction with team members and business units. Enthusiasm and flexibility to work on a variety of projects

WHAT YOU’LL NEED:

• Microsoft .NET (5–7 Years) Deep, well-rounded expertise across the complete software development lifecycle using .NET technologies. Consistently delivers end-to-end solutions — from requirements gathering through production deployment — within Agile/Scrum teams. Core stack: C#, ASP.NET Core, MVC, and Web API, utilizing Visual Studio IDE, SSRS, SOAP, XML, and GitHub. Strong understanding of advanced design patterns, API-first design, and SOLID principles.
• AWS (Cloud) Hands-on experience deploying and managing cloud infrastructure on AWS — covering compute, storage, serverless, and observability. Able to work independently across the cloud stack, moving beyond basic service consumption to support real engineering needs.
• RESTful API Skilled in designing, building, and consuming secure RESTful APIs with a strong command of industry standards. Well-versed in OAuth2 authentication, OpenAPI/Swagger documentation, and API testing workflows using Postman.
• AI Integration Practical, hands-on experience embedding AI capabilities into production software — including LLM API integration, prompt engineering, and developing AI-adjacent features. Actively deepening this expertise as a core part of a modern engineering toolkit.
• Collaboration & Communication Effective communicator with strong interpersonal and critical thinking skills. Experienced working within cross-functional, global teams — handling client communication, issue management, deployment support, and technical documentation with confidence.

Good to have:

• Working experience on enterprise-level applications/products
• Working experience in React/Angular, REACT, KONG, JIRA
• Experience with Web-based software as a service (SaaS) application
• Knowledge of Redis Cache for in-memory data structure storage and caching

WHAT’S IN IT FOR YOU?

At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

Key Responsibilities

As a AI Engineer/Senior AI Engineer and a key member of our engineering team in India, you will be responsible for designing, building, and owning the end-to-end lifecycle and release of our most critical AI-powered features within a microservices architecture. This role requires a balance of advanced technical depth in AI/ML and a strong sense of product ownership, ensuring our solutions deliver tangible user value at scale.

1. End-to-End AI System Ownership

• Design & Development: Design, build, and deploy production-grade AI systems, ranging from traditional Machine Learning models to modern LLM-powered features.
• Architecture & Deployment: Lead AI projects from concept to execution, including designing robust microservice architectures, modeling, rigorous evaluation, and secure deployment on AWS.
• Data Expertise: Work extensively with unstructured data, chunking, embeddings, vector databases (e.g., Pinecone, pgvector), and address complex real-world data quality challenges.
• Production Standards: Own the release process end-to-end, applying high engineering standards to ensure scalability, operability, and maintainability, aligning with Enboarder’s microservices philosophy.

1. Generative AI & LLM Focus

• LLM Integration: Evaluate, integrate, and operationalize LLM-based tools and APIs, including but not limited to Anthropic Claude and AWS Bedrock, to enhance product capabilities.
• Advanced Techniques: Apply expertise in prompt engineering, Retrieval-Augmented Generation (RAG), and advanced evaluation metrics for generative outputs.
• Agentic Systems: Explore and implement agentic AI frameworks, workflow orchestration (e.g., Langgraph, CrewAI, StrandsAgents), or multi-agent systems to automate complex user journeys.

1. Collaboration, Leadership, and Strategy

• Product Collaboration: Collaborate closely with product, design, and other engineering teams to translate business requirements into high-impact AI capabilities that drive measurable user and business outcomes.
• Technical Leadership: Stay updated on the latest AI/ML advancements, contribute to the company’s long-term technical strategy, and evaluate new technologies for adoption.
• Mentorship: Actively mentor and guide junior AI engineers, fostering a culture of technical excellence, clean code practices, and continuous experimentation.

Required Skills & Experience

• Total Experience: 6+ years of professional experience in the IT/Technology industry, with a substantial focus on building and deploying production systems.
• AI/ML Experience: 4+ years of direct experience in building and deploying ML or LLM-based systems in production environments, ideally within a high-traffic SaaS environment.
• Programming Mastery: Strong proficiency in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, scikit-learn).
• Generative AI Tooling: Hands-on experience with LLM-based frameworks such as LangChain, AWS Bedrock, or comparable in-house/open-source solutions.
• Vector Databases: Practical experience working with vector databases (e.g., FAISS, Pinecone, PGVector) for scalable similarity search and RAG implementation.
• Cloud Architecture: Extensive experience deploying, monitoring, and operating applications on AWS, demonstrating deep awareness of scalability, security, and cost-optimization in a microservices environment.

Preferred Qualifications (Nice to Have)

• Familiarity with FastAPI and containerization technologies (Docker, Kubernetes).
• Experience with MLOps tools such as MLflow, Airflow, or similar workflow orchestration platforms.
• Ability to balance technical trade-offs between model performance, inference cost, and system complexity in AI deployments.
• Direct experience with Fine Tuning or Pre-training large language models (LLMs) on domain-specific data.

*NOTE:* Hybrid work with 3 days in office.