BOLD is seeking a senior professional to implement and run Testing and Quality Assurance specifically designed for AI-driven products and Data Science workflows. In this role, you will bridge the gap between traditional software testing and modern machine learning evaluation. You have a great team management and organizational skills. You’ll have a broad mastery of capabilities, techniques, technologies and tools in the Testing and QA domains. You’ll be handling QA teams of various sizes and expertise.

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 up to to date with technology.

WHAT YOU’LL DO 

• Develop and own the QA strategy for AI-driven features, focusing on model accuracy, data drift, and performance metrics (Precision, Recall, F1-score).
• Implement state-of-the-art AI tools (e.g., GitHub Copilot, or custom LLM agents) to automate test case generation, code analysis, and synthetic data creation.
• Oversee the testing of Generative AI outputs, implementing "LLM-as-a-judge" frameworks to evaluate hallucination rates, toxicity, and prompt adherence.
• Develop and own BOLD’s quality framework from product development through to production
• Should be able to drive the initiatives (both Business and QA) in his area along with needed smooth coordination across the board to ensure a timely achievement of goal.
• Take part in Requirement Analysis, Sprint planning, Bug triage meetings.
• Liaise with product, development, and infrastructure teams to collaborate on delivery of high quality, high performance, and high availability applications
• Develop quality scripts with needed coverage to ensure defect free releases.
• Manage and mentor team members to maximize output and efficiency and promote a team culture of quality and fun
• Motivate, Encourage, Guide Teams maintaining equilibrium and satisfaction level.
• Give technical/logical solutions to problems faced by the teams and remove hurdles blocking releases.
• Evaluate and suggest new tools and technologies

WHAT YOU’LL NEED

• Solid understanding of the Machine Learning lifecycle (EDA, Training, Evaluation, Deployment).
• Experience using LLMs (GPT, Claude, Llama) and AI-coding assistants to accelerate the testing lifecycle.
• Experience in a high volume, high throughput web/ecommerce environment.
• Hands-on experience with UI/API automation (Selenium, Playwright, or Cypress) integrated with AI-driven healing capabilities.
• Experience with web service technology like XML, REST, SOAP
• Knowledge on any of the query language like SQL, JQL etc.
• Experience in testing complex web and mobile apps.
• Strong application architecture and technical knowledge
• Strong knowledge of web concepts, including web performance infrastructure.
• Able to play the role of a scrum master, with strong coordination skills
• Knowhow of basic UX standards, SEO/ SEM concepts and key tracking matrices
• Strong communication skills 

EXPERIENCE- 

• Module Lead, QA (AI/ML & Automation)- 5 years+

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

Head of Quality Engineering to lead and scale our QA function in India (Relocation to Noida required) 

 This is a pivotal leadership role within our Engineering and Technology team, requiring a unique blend of strategic foresight, commercial awareness, and hands-on technical expertise. 

The ideal candidate is not just a manager but a leader and coach—someone who can recruit and build a high-performing team from the ground up while maintaining involvement in projects and automation. You will be the driving force behind our continued AI Transformation in QA in the region and, ensure our technical capabilities are always one step ahead of business demand. 

This role offers relocation to Noida, its important that you are happy to relocate to Noida and our team will support your relocation 

What you’ll be doing: 

Leadership, Team Development & Future-Readiness 

• Build & Scale: Recruit top-tier QA talent to build the India team. Manage high-volume, high-pressure hiring cycles and  a establish QA Automation hub. 

• Future-Proofing the Workforce: Collaborate closely with Sales and Business Development teams to understand the sales pipeline and emerging market trends. Translate these insights into training roadmaps to ensure the team is "project-ready" for next-generation work before it arrives. 

• Talent Development: Follow and contribury to global engineering career progression frameworks. Foster a culture of continuous learning by coordinating training programs, onboarding graduates, and personally coaching team members. 

• Global Collaboration: Act as the primary liaison for the India region within our global community of QA leaders, ensuring alignment with global standards while addressing local operational needs. 

• Employee Wellbeing: Balance the drive for high performance with a deep commitment to team wellbeing, proactively managing signs of burnout and ensuring a healthy, sustainable work-life balance for your staff. 

 
AI Transformation & Technical Excellence 

• AI Leadership: Champion the adoption of AI-assisted testing tools and generative AI within the QA workflow. Lead transformation activities to automate test generation, self-healing scripts, and predictive quality analytics. 

• Automation Strategy: Lead the design and development of robust, scalable test automation frameworks using modern tools, with a specific focus on Playwright. 

• Hands-on Engineering: Review complex test scenarios and contribute to automation code or framework architecture. You will be expected to guide the team on technical implementation in Java, Python, or JavaScript. 

• Shift-Left & CI/CD: Support project teams in integrating quality gates within deployment pipelines and drive the adoption of "Shift-Left" testing principles. 

 
Strategic Quality Management 

• Metrics & KPIs: Define and track quality metrics (DRE, Test Coverage, Cycle Time) to provide transparent reporting to executive stakeholders. 

• SDLC Integration: Collaborate closely with Engineering, Product, and DevOps leads to embed quality as a mindset throughout the development lifecycle. 

• Infrastructure & Data: Oversee test environment management, data management strategies, and ensure the infrastructure supports rigorous performance and security testing. 

• Client Delivery Assurance: Act as the senior escalation point for critical project quality issues. Build relationships with global account leads to ensure Indian based delivery teams are meeting client expectations and strictly adhering to any SLAs 

 
Process & Operations 

• Agile Efficiency: Optimize testing processes to support rapid Agile/Scrum development cycles, reducing time-to-market whilst improving quality. 

• Prioritization: Expertly handle multiple conflicting priorities and context switching between strategic planning, crisis management, and recruitment activities. 

What we want from you: 

• Extensive QA Leadership & Team Scaling: Proven extensive experience in Quality Assurance, leading and managing teams, with a track record of building and scaling QA teams from small to medium sizes (including graduate intake and senior hires). 

• Comprehensive Technical QA Expertise: Strong hands-on proficiency in test automation frameworks (Java, Python, JavaScript), deep understanding of Functional, API, Performance (JMeter, k6), and Security testing fundamentals. 

• Modern QA Tooling & CI/CD Mastery: Experience with Playwright is highly desirable, along with proficiency in modern CI/CD tools (Jenkins, GitHub Actions, GitLab CI). 

• E-commerce/Retail Domain Expertise: Understanding of complex buying journeys within E-commerce/Retail domains, with experience using platforms like Shopify, Adobe Commerce, SFCC, or CommerceTools. 

• Strategic Business & Commercial Acumen: Ability to analyse business trends, sales pipelines, and commercial impact to forecast skill requirements, drive proactive team upskilling, and strategically prepare teams for future sales initiatives. 

• AI Transformation & Empowerment: Proven experience with AI transformation activities and a passion for empowering teams to effectively utilize AI tools in daily workflows. 

• Adaptable, Resilient & Results-Oriented: Comfortable with frequent context switching, adept at managing ambiguity in a fast-paced environment, and capable of handling demanding hiring targets and delivery deadlines. 

• Exceptional Communication & Stakeholder Management: Excellent verbal and written communication skills, capable of clearly explaining complex technical quality risks to non-technical stakeholders. 

• High Emotional Intelligence & Relationship Building: Possesses high emotional intelligence, fostering deep trust and strong relationships across cultural boundaries as an approachable, empathetic listener. 
• Vibrant Team & Tech Community Builder: Actively fosters a vibrant internal engineering culture (organizing Hackathons, Guilds, Lunch & Learns) and a strong sense of community within a distributed workforce through team bonding and celebrating successes. 

Desirable Attributes: 

• Cloud Native: Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). 

• Emerging Tech: Demonstrated knowledge of AI/ML testing approaches and implementation of LLMs in testing. 

• Certifications: ISTQB Advanced Level or equivalent quality certifications. 

• Remote Management: Experience managing distributed or remote teams across different time zones. 

What we can offer you:

Alongside the opportunity to work with some of the most exciting brands around the world, we’ll also prioritise your career development and help you grow your skills. We’ll empower you to make a difference, allow you to be yourself, and respect who you are.

Our culture thrives on our core values, designed for impact-driven individuals: Heart, Brains and Courage.

We lead with Heart, fostering empathy and trust where genuine connections and human-centric work flourish.
We empower your Brains for innovation, valuing relentless curiosity and collaborative intelligence to solve complex challenges.
And we champion Courage, inspiring you to speak up, embrace experimentation, and advocate for bold solutions that push our thinking to be better than yesterday.

AT VML Enterprise Solutions

Our Enterprise Solutions division houses strategic consultants, creative and technical architects and skilled developers and operators that together help some of the world’s leading organisations to deliver outstanding digital experiences across all major routes to market worldwide: marketplaces, online retailers, D2C, B2B and social platforms. With over 4,200 experts in 55 operational centres across 34 countries, our capabilities span the entire buying journey from customer acquisition, through engagement, to conversion and loyalty, driving multi-channel growth for world-leading brands.

We work with some of the most exciting brands such as The Coca-Cola Company, EY, Bosch, Unilever, Ford, DFS, Mercedes-Benz, Johnson & Johnson, Nestlé, Sainsbury’s, Selfridges, Shell and Tiffany & Co. We’ve built over 500 platforms for brands and retailers and generate in excess of $29bn annually for our clients and work with over 50 strategic partners including Adobe, SAP, Salesforce, HCL, Shopify, Sitecore, BigCommerce, commerce tools and Acquia. Our reputation is based on our people, and we believe we have some of the best in the business.

As our business grows internationally, we’re looking for new people to join us on our journey to inspire and take a key role in shaping some of the best commerce solutions, services, and websites in the world. Working as a team, no problem is insurmountable; we share in our client’s successes and believe that anyone can show creative bravery no matter what their role is in the team.

Head of Quailify Engineering needed to lead and scale our QA function in India. This is a pivotal leadership role within our Engineering and Technology team, requiring a unique blend of strategic foresight, commercial awareness, and hands-on technical expertise. 

The ideal candidate is not just a manager but a leader and coach—someone who can recruit and build a high-performing team from the ground up while maintaining involvement in projects and automation. You will be the driving force behind our continued AI Transformation in QA in the region and, ensure our technical capabilities are always one step ahead of business demand. 

What you’ll be doing: 

Leadership, Team Development & Future-Readiness 

• Build & Scale: Recruit top-tier QA talent to build the India team. Manage high-volume, high-pressure hiring cycles and  a establish QA Automation hub. 

• Future-Proofing the Workforce: Collaborate closely with Sales and Business Development teams to understand the sales pipeline and emerging market trends. Translate these insights into training roadmaps to ensure the team is "project-ready" for next-generation work before it arrives. 

• Talent Development: Follow and contribury to global engineering career progression frameworks. Foster a culture of continuous learning by coordinating training programs, onboarding graduates, and personally coaching team members. 

• Global Collaboration: Act as the primary liaison for the India region within our global community of QA leaders, ensuring alignment with global standards while addressing local operational needs. 

• Employee Wellbeing: Balance the drive for high performance with a deep commitment to team wellbeing, proactively managing signs of burnout and ensuring a healthy, sustainable work-life balance for your staff. 

 
AI Transformation & Technical Excellence 

• AI Leadership: Champion the adoption of AI-assisted testing tools and generative AI within the QA workflow. Lead transformation activities to automate test generation, self-healing scripts, and predictive quality analytics. 

• Automation Strategy: Lead the design and development of robust, scalable test automation frameworks using modern tools, with a specific focus on Playwright. 

• Hands-on Engineering: Review complex test scenarios and contribute to automation code or framework architecture. You will be expected to guide the team on technical implementation in Java, Python, or JavaScript. 

• Shift-Left & CI/CD: Support project teams in integrating quality gates within deployment pipelines and drive the adoption of "Shift-Left" testing principles. 

 
Strategic Quality Management 

• Metrics & KPIs: Define and track quality metrics (DRE, Test Coverage, Cycle Time) to provide transparent reporting to executive stakeholders. 

• SDLC Integration: Collaborate closely with Engineering, Product, and DevOps leads to embed quality as a mindset throughout the development lifecycle. 

• Infrastructure & Data: Oversee test environment management, data management strategies, and ensure the infrastructure supports rigorous performance and security testing. 

• Client Delivery Assurance: Act as the senior escalation point for critical project quality issues. Build relationships with global account leads to ensure Indian based delivery teams are meeting client expectations and strictly adhering to any SLAs 

 
Process & Operations 

• Agile Efficiency: Optimize testing processes to support rapid Agile/Scrum development cycles, reducing time-to-market whilst improving quality. 

• Prioritization: Expertly handle multiple conflicting priorities and context switching between strategic planning, crisis management, and recruitment activities. 

What we want from you: 

• Extensive QA Leadership & Team Scaling: Proven extensive experience in Quality Assurance, leading and managing teams, with a track record of building and scaling QA teams from small to medium sizes (including graduate intake and senior hires). 

• Comprehensive Technical QA Expertise: Strong hands-on proficiency in test automation frameworks (Java, Python, JavaScript), deep understanding of Functional, API, Performance (JMeter, k6), and Security testing fundamentals. 

• Modern QA Tooling & CI/CD Mastery: Experience with Playwright is highly desirable, along with proficiency in modern CI/CD tools (Jenkins, GitHub Actions, GitLab CI). 

• E-commerce/Retail Domain Expertise: Understanding of complex buying journeys within E-commerce/Retail domains, with experience using platforms like Shopify, Adobe Commerce, SFCC, or CommerceTools. 

• Strategic Business & Commercial Acumen: Ability to analyse business trends, sales pipelines, and commercial impact to forecast skill requirements, drive proactive team upskilling, and strategically prepare teams for future sales initiatives. 

• AI Transformation & Empowerment: Proven experience with AI transformation activities and a passion for empowering teams to effectively utilize AI tools in daily workflows. 

• Adaptable, Resilient & Results-Oriented: Comfortable with frequent context switching, adept at managing ambiguity in a fast-paced environment, and capable of handling demanding hiring targets and delivery deadlines. 

• Exceptional Communication & Stakeholder Management: Excellent verbal and written communication skills, capable of clearly explaining complex technical quality risks to non-technical stakeholders. 

• High Emotional Intelligence & Relationship Building: Possesses high emotional intelligence, fostering deep trust and strong relationships across cultural boundaries as an approachable, empathetic listener. 
• Vibrant Team & Tech Community Builder: Actively fosters a vibrant internal engineering culture (organizing Hackathons, Guilds, Lunch & Learns) and a strong sense of community within a distributed workforce through team bonding and celebrating successes. 

Desirable Attributes: 

• Cloud Native: Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). 

• Emerging Tech: Demonstrated knowledge of AI/ML testing approaches and implementation of LLMs in testing. 

• Certifications: ISTQB Advanced Level or equivalent quality certifications. 

• Remote Management: Experience managing distributed or remote teams across different time zones. 

What we can offer you:

Alongside the opportunity to work with some of the most exciting brands around the world, we’ll also prioritise your career development and help you grow your skills. We’ll empower you to make a difference, allow you to be yourself, and respect who you are.

Our culture thrives on our core values, designed for impact-driven individuals: Heart, Brains and Courage.

We lead with Heart, fostering empathy and trust where genuine connections and human-centric work flourish.
We empower your Brains for innovation, valuing relentless curiosity and collaborative intelligence to solve complex challenges.
And we champion Courage, inspiring you to speak up, embrace experimentation, and advocate for bold solutions that push our thinking to be better than yesterday.

AT VML Enterprise Solutions

Our Enterprise Solutions division houses strategic consultants, creative and technical architects and skilled developers and operators that together help some of the world’s leading organisations to deliver outstanding digital experiences across all major routes to market worldwide: marketplaces, online retailers, D2C, B2B and social platforms. With over 4,200 experts in 55 operational centres across 34 countries, our capabilities span the entire buying journey from customer acquisition, through engagement, to conversion and loyalty, driving multi-channel growth for world-leading brands.

We work with some of the most exciting brands such as The Coca-Cola Company, EY, Bosch, Unilever, Ford, DFS, Mercedes-Benz, Johnson & Johnson, Nestlé, Sainsbury’s, Selfridges, Shell and Tiffany & Co. We’ve built over 500 platforms for brands and retailers and generate in excess of $29bn annually for our clients and work with over 50 strategic partners including Adobe, SAP, Salesforce, HCL, Shopify, Sitecore, BigCommerce, commerce tools and Acquia. Our reputation is based on our people, and we believe we have some of the best in the business.

As our business grows internationally, we’re looking for new people to join us on our journey to inspire and take a key role in shaping some of the best commerce solutions, services, and websites in the world. Working as a team, no problem is insurmountable; we share in our client’s successes and believe that anyone can show creative bravery no matter what their role is in the team.

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

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 an Solutions Engineer, you will actively contribute to, architect for, and lead the company in the design and development of new infrastructure automation projects. You will be instrumental in helping us solve, by architecture and implementation, complex hybrid infrastructure problems among corporate’s robust inventory of networking systems, applications, and cloud infrastructure. You will work closely with a team of highly skilled individuals to deliver on high impact engagements at Sumo Logic, reporting directly to the Global Head of Infrastructure and Data and engaging on projects under the guidance of the Lead Solution Architect..

You are a strong solutions engineer who is passionate about scalable, resilient, secure, and cost-efficient infrastructure solutions. You care about producing clean, elegant, maintainable, robust, well-tested code; you do this as a member of a team, helping the group come up with a better solution than you would as an individual. Ideally, you have experience with performance, scalability, and reliability issues of 24x7 uptime systems and solutions.

Responsibilities:

• Designing and implementing complex and well-architected enterprise infrastructure and data solutions
• Work to improve existing systems, solutions, and process through architectural reviews and design enhancement initiatives
• Experience in devops methodologies and practices as applied to infrastructure, cloud, identity, integration and network solutions
• Improve systems to provide strict compliance adherence, security guardrails, and cost-optimization
• Contribute to the re-architecting of systems, solutions, and processes for more streamlined, scalable, and resilient implementations
• Contribute to well-architected, end-to-end provisioning solutions to a growing enterprise organization across multiple environments and types of infrastructure
• Build strong partnerships and engage with other teams at Sumo Logic to create solutions that enable and benefit all parties and increased derived value

Requirements:

• 3+ years of industry experience with a proven track record of ownership and delivery
• Experience developing scalable, secure, and resilient infrastructure architectures and implementations
• Experience in observability and cost-optimization in application, server, and cloud (AWS preferred) settings
• Experience working with on-premise (Fortinet) network devices on a system administration and configuration level
• Experience with DNS (CloudFlare and Route53 preferred) as well as VPN management (FortiClient, ZScaler, and Netskope preferred)
• Experience with Identity Providers (Okta preferred)
• Experience with Certificate Management (Digicert and AWS ACM preferred) and authentication 
• Hands-on infrastructure as code experience (Terraform preferred) as well as CI/CD pipelines (Scalr and GitHub Actions preferred)
• Experience with writing automations and system integrations (Python preferred)
• Strong experience with AWS
• Excellent verbal and written communication skills
• Experience implementing robust and well-architected designs for enterprise scale systems
• Experience and comfort with an on-call schedule for enterprise systems during daylight hours regional time

Desirable:

• Experience in the following specific technologies is a plus:
• ADP
• Azure
• GCP
• Experience with Scalr
• Experience with AI tooling such as Boomi, Databricks (AI portions), AWS Bedrock, Gemini, and Claude
• Experience with Databricks as a whole
• CCNA, CCNP, or equivalent network certifications
• You should have a passion for continuous learning and deep technological curiosity
• Agile development experience and a familiarity with Jira, sprints, and pointing

About Us:

Sumo Logic, Inc., empowers the people who power modern, digital business.  Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its SaaS analytics platform. The Sumo Logic Continuous Intelligence Platform™ helps practitioners and developers ensure application reliability, secure, and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.

BOLD is seeking for the 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 NLP, large language models, predictive modelling, 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 
• Collaborates effectively with cross-functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Estimates efforts, identify risks, devises and meets project schedules. 
• Runs review meetings effectively and drive the closure of all open issues on time. 
• Evolve prompt engineering applications and benchmark different Large Language models to solve business problems.                  
• Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. 
• Implement and experiment with agentic workflows to improve the job seeker experience. 
• Rises above detail to see broader issues and implications for whole product/team.  

WHAT YOU’LL NEED

• Should be able to handle a team of 2-5 members, if required. 
• 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.  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Experience in using large language models. 
• Experience with distributed, semantic and vector based search and match systems.  
• Experience with prompt engineering, chain-of-thought, retrieval augmented generation, vector databases and preferably LLM agents. 
• Experience in feature selection, building and optimizing classifiers. 
• Experience with software stack components, including common programming languages, back-end technologies, database modelling, continuous integration, services-oriented architecture, software testability, etc. 
• Langchain and/or Llamaindex. 
• Be a keen learner and enthusiastic about developing software. 
   

EXPERIENCE- 

• Project Lead, Data Science- 8 years+

#LI-SV1

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 NLP, large language models, predictive modelling, 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 
• Collaborates effectively with cross functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Estimates efforts, identify risks, devises and meets project schedules. 
• Runs review meetings effectively and drive the closure of all open issues on time 
• Mentors/coaches data scientists to facilitate their development and provide technical leadership to them. 
• Rises above detail to see broader issues and implications for whole product/team. 

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 Solr/OpenSearch/Elasticsearch .
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Experience with embedding & vector search  
• Experience in using large language models. 
• 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- 

• Module Lead, Data Science- 5.5 years

#LI-SV1

BOLD is seeking for the 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 

• Build AIML models that serve for content generation, content recommendation, and content moderation using LLMs. 
• Responsible for converting business requirements into robust data science algorithms. 
• Responsible for providing technical leadership to a team of data science engineers. 
• Responsible for design, development, deployment of AI/ML, NLP, statistical & content recommendation algorithms that may not require LLMs.  
• 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 
• Collaborates effectively with cross functional teams to deliver end-to-end products & features. 
• Demonstrates ability to multi-task and re-prioritize responsibilities based on changing requirements. 
• Responsible for creating model validation framework. 
• Leading a data science team that delivers actionable results through the combination of data science solutions, business skills, statistical knowledge, and understanding of data. 
• Distilling complex analytical results into presentable, digestible, and actionable feedback for product and engineering teams. 
• Recruit, build and retain a top-tier data science team that brings together top talent at all levels, cutting edge technology, and analytic innovation. 
• Assess, inspire and motivate a high performing team of data science professionals. 

WHAT YOU’LL NEED

• Proven experience in solving open-ended business problems using data-science/ML/AI from initial ideation stage up to delivering the ready-to-use solution. 
• Strong Programming experience in Python. Familiar with various Machine Learning algorithms and Statistical methods. 
• 10+ yrs of working experience in MLData science with NLP background  
• Experience with frameworks that optimizes prompt engineering (langChain/crewai/etc) 
• Must have delivered multiple data science product(s) in production. Deployment with LLMs is a plus. 
• Practical LLM/RAG experience for search quality  such as  query understanding, semantic retrieval, reranker design .  
• Experience with Solr/OpenSearch/Elasticsearch … 
• Experience with embedding & vector search  
• Experience designing and implementing ML systems with Data Pipelines (Data Cleaning and creative Feature Engineering), Model Iterations and Evaluation, High throughput ML(Model Training, Evaluation, GPU vs CPU, XGBoost ML), Python ML Libs(TensorFlow, PyTorch). 
• Experience in leading a team of 3-5 data scientists. 
• Experience using tools to deploy models into the production environment such as Jenkins 

 EXPERIENCE- 

• Engineering Manager, Data Science- 10 years+

#LI-SV1

Who You Are:

We’re building a next-generation Product Operations function to help our growing organization scale efficiently — and we’re looking for an ambitious, detail-oriented Associate Product Operations Manager to be part of this journey.

As an early member of the Product Ops team, you will play a critical role in designing scalable workflows, embedding AI-driven efficiencies, and enabling high-velocity product development. You’ll work at the intersection of Product, Engineering, and AI, helping teams operate smarter through automation, structured processes, and intelligent tooling.

This is a hands-on role ideal for someone who understands how modern product organizations leverage AI, automation, and data to drive impact.

What You Will Do:

Process Design, AI Integration & Workflow Automation

• Partner with Product, Engineering, and AI teams to design, document, and optimize product development workflows.
• Identify repetitive/manual processes and implement workflow automation using AI and collaboration tools and integrations.
• Contribute to building AI-powered operational use cases (e.g., automated reporting, requirement summarization, sprint insights, ticket classification).
• Support implementation of frameworks across:
  • Roadmap planning
  • Sprint Cycles
  • Release Management
  • Product Reviews
• Continuously improve processes to enhance speed, quality, and scalability.

Product Lifecycle & Agile Operations

• Support and optimize the end-to-end product lifecycle in an Agile environment.
• Work closely with Product Managers to improve planning, prioritization, and execution hygiene.

Data

• Collect and organize product metrics and performance data Build dashboards and reporting systems to track:
  • Product Performance
  • Project Status
  • Operational KPIs
• Assist in tracking and communicating progress toward key product and business goal

Cross-Functional Collaboration

• Act as a connector between Product, Engineering, AI/ML, and GTM teams.
• Collaborate on AI solutioning and tooling initiatives to improve product operations.
• Facilitate alignment, maintain documentation, and ensure accountability across teams.

Tools Setup, Governance & Optimization

• Help manage and optimize core product management and collaboration tools (e.g., Jira, Airtable, Confluence) and AI productivity tools (e.g., LLM-based assistants, automation platforms)
• Ensure data integrity, process compliance, and scalable tool usage.
• Research, evaluate and implement new tools to improve efficiency and automation maturity.
• Support the rollout of new tools, systems, and processes across the organization.

What You will Need:

Required Qualifications:

• Bachelor’s/Master’s degree in Business, Engineering, Information Systems, or related field.
• 3–4 years of experience in Product Operations, Business Operations, or Process Improvement roles.
• Strong understanding of:
  • Product lifecycle in Agile environments
  • Workflow automation concepts and tools
• Hands-on or working knowledge of:
  • AI tools (e.g., ChatGPT, Claude, automation tools, AI copilots
  • AI use cases in product or business workflows
• Experience collaborating with Product, Engineering, and/or AI teams.
• Hands on with tools like Jira, Airtable, Confluence.
• Strong analytical, problem-solving, and documentation skills.
• Excellent written and verbal communication.
• A proactive mindset — eager to take ownership and learn in a fast-paced, evolving environment.
• Experience working in or with technology-driven organizations.

Preferred Qualifications (Good to have):

• Hands-on experience building automation workflows (Zapier, Make, APIs, scripts, etc.).
• Experience in AI implementation within business or product workflows.
• Exposure to product analytics tools (e.g., Pendo, Mixpanel, Amplitude).
• Understanding of data structures, APIs, or system integrations.

Soft Skills:

• Highly collaborative and comfortable working across multiple teams and functions.
• Curious, data-driven, and eager to experiment with new systems or workflows.
• Strong sense of ownership and accountability.
• Adaptable to change and comfortable in a startup or fast-growth environment.

Why This Role Is Exciting:

• Shape the foundation of a fast-growing Product Operations team and have a lasting impact on how the company scales.
• Gain exposure to all parts of the product lifecycle — from strategy and execution to launch and iteration.
• Work closely with Product, Engineering, and Leadership on high-visibility initiatives.

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, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability.

^#LI-RS1

WHO YOU ARE:

We’re seeking a forward-thinking AI Product Manager with strong technical depth in Machine Learning, LLM-based products, Automation, and API-driven platform design. In this role, you will define, build, and scale AI-powered solutions across Zinnia’s digital insurance platform, enhancing underwriting, claims, operations, and customer engagement workflows.

You’ll work at the intersection of AI innovation, insurance expertise, and engineering execution, translating business needs into scalable products that deliver measurable impact.

WHAT YOU’LL DO:

• Contribute to the product vision and roadmap for AI/ML initiatives across Zinnia’s platform.
• Identify high-impact opportunities to integrate AI into insurance value chains (underwriting, policy admin, claims, distribution, agent enablement).
• Evaluate new AI technologies - Agentic AI, Gen AI (LLMs, RAG, predictive analytics, automation frameworks) and drive adoption across the organization.
• Translate user problems and business needs into clear product requirements, PRDs, and user stories.
• Work closely with engineering, data science, design, actuarial, and insurance SMEs to ship high-quality AI products.
• Drive API-first development for system integrations with carriers, distributors, third-party data providers, and internal platforms.
• Ensure AI and APIs follow robust security, compliance, and governance guidelines—especially relevant to Life & Annuities.

AI/ML Technical Collaboration:

• Understand ML lifecycle basics (data pipelines, model drift, monitoring, inference performance).
• Work with engineers to design and expose AI capabilities via scalable APIs and microservices.

WHAT YOU’LL NEED:

• A Bachelor's/Master's Degree with 5-8 years of Product Management experience, with at least 2–3 years in Agentic AI, Gen AI, AI/ML, data products, or automation-based products.
• Experience working with APIs, microservices, and modern cloud architectures (AWS/Azure/GCP).
• Ability to write detailed requirements for API integrations, data flows, and AI capabilities.
• Strong understanding of ML concepts (classification, NLP/LLMs, predictive models, evaluation metrics).
• Proven ability to work with Data Science and Engineering teams in a deeply technical environment.
• Strong problem-solving skills with a bias for experimentation, iteration, and measurable output.
• Excellent communication skills, especially in simplifying complex AI concepts for non-technical stakeholders.

Preferred Qualifications:

• Experience in InsurTech, Life & Annuities, financial services, or regulated industries.
• Familiarity with underwriting data sources (e.g., Rx, MIB, credit), claims/operations automation, or distribution workflows.
• Experience with LLM products, vector databases, prompt engineering, or RAG systems.
• Exposure to compliance frameworks related to AI ethics, data privacy, and model governance.

WHAT’S IN IT FOR YOU?

Zinnia offers excellent career progression and competitive compensation. We offer great benefits, including health/dental insurance, parental leave, profit sharing, PF, incentive/bonus opportunity, tuition reimbursement, and so much more. We’re looking for the best and brightest innovators in the industry to join our team. 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-RS1

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.

Responsibilities:
○ Design and develop new software applications from scratch
○ Work with developers and other teams across the company to build new features and tools.
○ Add new product features using Python language.
○ Write code which is micro services complaint and can be reused.
○ Own problems end-to-end, thinking through everything from user experience, data models, scalability, operability and ongoing metrics.
○ Uphold our high engineering standards and bring consistency to the codebases, infrastructure, and processes you will encounter.
○ Test and debug code, Monitor and troubleshoot production issues
○ Collaborate with experts in product, design, and operations.
○ Proactive and prompt analysis and identification of functional bugs and performance issues

Requirements:
○ Enjoy being a generalist, working on both the frontend, backend, and everything in between to tackle problems and delight customers.
○ Thinking about tools and services, and writing high quality code.
○ We write code using Python, React and other languages like javascript, typescript, nodejs, shell scripts, AWS cloud services.
○ We use productivity enhancement tools like copilot, cursor etc.
○ Strong knowledge of Databases (either NoSql or RDBMS), DynamoDB and postgres preferred.
○ Strong experience with REST API development, Flask API, and JSON handling.
○ Hands-on experience with Python frameworks or libraries (any of the following is a plus): PySpark, Pandas, NumPy, asyncio, etc.
○ Exposure to ML / GenAI workflows is a strong advantage (model integration, vector DBs, embeddings pipelines, etc.)
○ Unit testing of REST API and server side components on Python
○ Working on CI/CD pipeline.
○ Server caching optimisations using memcache, etc
○ Authentication mechanisms like SAML SSO, MFA, etc
○ If you have worked on Integrations across various systems using APIs or messages that experience will be good to have.
○ Taking pride in working on projects to successful completion, involving a wide variety of technologies and systems.
○ Putting yourself in the shoes of your users, and creating an intuitive, delightful experience.
○ You should have understanding around Security for Web Applications and backend processes. Security is very important for us.
○ Holding yourself and others to a high bar when working with production systems.
○ Stitching many different services and processes together, even if you have not worked with them before.
○ Strong understanding of front-end and back-end technologies
○ Experience working in an agile development environment
○ Knowledge of nodejs is nice-to-have, however not a must.

Experience
○ 4-7 years experience in the IT/Technology industry.
○ 4+ years of experience in Python
○ 3+ years of experience in NoSql / RDBMS, DynamoDB and postgres preferred.
○ 3+ years of experience in working on code version source control tools like Git
○ Experience in sonarqube, use of copilot or similar productivity enhancement tools

Engineering at Enboarder:
○ We work in an environment where it matters to make the right design decisions the first time, and as a result, take on less technical debt.
○ We roll out code to production every 2 weeks.
○ We’re big fans of micro services architecture and are moving a lot of products towards micro services.
○ We like to experiment with new features and do not see failures as bad, but building blocks for future features.
○ We use AWS as our Infrastructure and continually improve. We provide ample opportunities to learn and use new AWS features.
○ Product is a highly collaborative initiative across multiple teams. Engineers are expected to understand and have product input, designing systems towards our long-term product vision.
○ Our customers are fine with fewer features, but are not ok with broken features.
○ People have a strong sense of ownership and accountability for what they’re building.
○ What we build today will be the foundation for other systems in the future.
○ We are very frank on discussing technical matters. If one disagrees with how things are being done, we encourage them to speak up and help us get to the truth faster.

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

Bold is seeking a Devops professional who owns production ML environments and MLOps infrastructure within infrastructure and data science teams. Handle day-to-day support, ad-hoc requests, and cross-team projects. Architect scalable MLOps pipelines using AWS services like SageMaker, EMR, and OpenSearch.

ABOUT THIS TEAM

Infrastructure team provides various services including automation, observability, cloud/server/network architectures, CICD, infrastructure as code, database administration, incident management, vendor management, security and compliance, and acquiring new skills. These services help to improve efficiency, reduce errors, and ensure fast and reliable application releases while maintaining security and compliance. Techops help teams monitor applications and infrastructure, create resilient infrastructure, identify and resolve IT service issues, manage vendors, and ensure cloud security and compliance. The team also focuses on continuous learning and implementing new technologies to provide better value to the organization.

WHAT YOU’LL DO

• Architect and productionize microservices with advanced DevOps pipelines , partnering with data science/ML teams to optimize model serving on Kubernetes platforms with service mesh.
• Design comprehensive observability frameworks to minimize MTTR and ensure24x7platform reliability.
• Engineer secure, automated CI/CD workflows with governance and compliance controls
• Lead 24x7 on-call engineering, CDN & security hardening and cost optimization strategies IAAS & PAAS in Cloud
• Manage infrastructure operations, production deployments, and hybrid cloud environments.
• Drive cross-functional collaboration with development, QA, operations, and data teams across global time zones to scale OpenSearch/EMR platforms and platform operations

WHAT YOU’LL NEED

• 4.5+ years (Sr. Engineer) / 7+ years (Module Lead)AWS/DevOps production experience
• Scripting: Python/Bash/Groovy/Java(CI/CD, EKS, FastAPI/Spring Boot)
• CI/CD: Jenkins (declarative pipelines, Groovy),Spinnaker, CodePipeline /CodeBuild, Gradle, Maven, Artifactory, GitHub Actions
• IaC:Terraform, AWS CloudFormation
• Containers: EKS + Istio/ Gloo/ Karpenter, ECS, Docker, Buildah
• AWS: VPC/IAM/GuardDuty/AWS Config, S3/ DynamoDB /Lambda /SageMaker /EMR, cost optimization
• Observability: Splunk, CloudWatch, Prometheus/Grafana, New Relic, Azure Monitor
• GitHub: Actions automation, branch/PR governance
• DNS management (NS1/Cloudflare/GoDaddy)

EXPERIENCE-

• Sr. Engineer Devops AWS (Automation)- 4.5 years+

BOLD is seeking for Devops professional to own the production ML environments and MLOps infrastructure within infrastructure and data science teams. Handle day-to-day support, ad-hoc requests, and cross-team projects. Architect scalable MLOps pipelines using AWS services like SageMaker, EMR, and OpenSearch.

ABOUT THIS TEAM

Infrastructure team provides various services including automation, observability, cloud/server/network architectures, CICD, infrastructure as code, database administration, incident management, vendor management, security and compliance, and acquiring new skills. These services help to improve efficiency, reduce errors, and ensure fast and reliable application releases while maintaining security and compliance. Techops help teams monitor applications and infrastructure, create resilient infrastructure, identify and resolve IT service issues, manage vendors, and ensure cloud security and compliance. The team also focuses on continuous learning and implementing new technologies to provide better value to the organization.

WHAT YOU’LL DO

• Design and maintain end-to-end MLOps pipelines for data ingestion, feature engineering, model training, deployment, and monitoring. 
• Productionize ML/GenAI services, collaborating with data scientists on model serving and workflow optimization. 
• Implement monitoring, alerting, and observability to reduce MTTR and ensure production reliability. 
• Manage data/feature stores and search infrastructure for scalable ML inference. 
• Automate CI/CD for ML models and infrastructure with governance and security compliance. 
• Handle security patching, cost optimization, and 24x7 on-call rotations for critical services. 
• Coordinate cross-functionally with development, QA, ops, and data teams to innovate build/deployment processes.​ 

WHAT YOU’LL NEED

• 4.5+ years (Sr Engineer)/7+ years (Module Lead) in AWS MLOps with hands-on SageMaker (Pipelines, Model Registry, Studio), EMR, OpenSearch (kNN/vector search). 
• Python/Bash scripting for CI/CD, provisioning, monitoring of  FastAPI/Spring Boot web services; and Linux servers (Solr/OpenSearch). 
• AWS services (S3, DynamoDB, Lambda, Step Functions) with cost control, reporting; databases (MySQL, MongoDB). 
• Strong Linux and networking fundamentals;  
• Hands-on expertise in ML tools (MLFlow, Airflow, Metaflow, ONNX).​ 

EXPERIENCE-

• MLOps Sr. Engineer, DevOps - 4.5+ years 

#LI-SV1