Scientist - Natural Language Processing Engineer

Certa (getcerta.com) is a Silicon Valley-based startup automating the vendor, supplier, and stakeholder onboarding processes for businesses globally. Serving Fortune 500 and Fortune 1000 clients, Certa's engineering team tackles expansive and deeply technical challenges, driving innovation in business processes across industries.

Location: Remote (India only)

Role Overview

We are looking for an experienced and innovative AI Engineer to join our team and push the boundaries of large language model (LLM) technology to drive significant impact in our products and services . In this role, you will leverage your strong software engineering skills (particularly in Python and cloud-based backend systems) and your hands-on experience with cutting-edge AI (LLMs, prompt engineering, Retrieval-Augmented Generation, etc.) to build intelligent features for enterprise (B2B SaaS). As an AI Engineer on our team, you will design and deploy AI-driven solutions (such as LLM-powered agents and context-aware systems) from prototype to production, iterating quickly and staying up-to-date with the latest developments in the AI space . This is a unique opportunity to be at the forefront of a new class of engineering roles that blend robust backend system design with state-of-the-art AI integration, shaping the future of user experiences in our domain.

Key Responsibilities

• Design and Develop AI Features: Lead the design, development, and deployment of generative AI capabilities and LLM-powered services that deliver engaging, human-centric user experiences . This includes building features like intelligent chatbots, AI-driven recommendations, and workflow automation into our products.
• RAG Pipeline Implementation: Design, implement, and continuously optimize end-to-end RAG (Retrieval-Augmented Generation) pipelines, including data ingestion and parsing, document chunking, vector indexing, and prompt engineering strategies to provide relevant context to LLMs . Ensure that our AI systems can efficiently retrieve and use information from knowledge bases to enhance answer accuracy.
• Build LLM-Based Agents: Develop and refine LLM-based agentic systems that can autonomously perform complex tasks or assist users in multi-step workflows. Incorporate tools for planning, memory, and context management (e.g. long-term memory stores, tool use via APIs) to extend the capabilities of our AI agents . Experiment with emerging best practices in agent design (planning algorithms, self-healing loops, etc.) to make these agents more reliable and effective.
• Integrate with Product Teams: Work closely with product managers, designers, and other engineers to integrate AI capabilities seamlessly into our products, ensuring that features align with user needs and business goals . You’ll collaborate cross-functionally to translate product requirements into AI solutions, and iterate based on feedback and testing.
• System Evaluation & Iteration: Rigorously evaluate the performance of AI models and pipelines using appropriate metrics – including accuracy/correctness, response latency, and avoidance of errors like hallucinations . Conduct thorough testing and use user feedback to drive continuous improvements in model prompts, parameters, and data processing.
• Code Quality & Best Practices: Write clean, maintainable, and testable code while following software engineering best practices . Ensure that the AI components are well-structured, scalable, and fit into our overall system architecture. Implement monitoring and logging for AI services to track performance and reliability in production.
• Mentorship and Knowledge Sharing: Provide technical guidance and mentorship to team members on best practices in generative AI development . Help educate and upskill colleagues (e.g. through code reviews, tech talks) in areas like prompt engineering, using our AI toolchain, and evaluating model outputs. Foster a culture of continuous learning and experimentation with new AI technologies.
• Research & Innovation: Continuously explore the latest advancements in AI/ML (new model releases, libraries, techniques) and assess their potential value for our products . You will have the freedom to prototype innovative solutions – for example, trying new fine-tuning methods or integrating new APIs – and bring those into our platform if they prove beneficial. Staying current with emerging research and industry trends is a key part of this role .

Required Skills and Qualifications

• Software Engineering Experience: 3+ years (Mid-level) / 5+ years (Senior) of professional software engineering experience. Rock-solid backend development skills with expertise in Python and designing scalable APIs/services. Experience building and deploying systems on AWS or similar cloud platforms is required (including familiarity with cloud infrastructure and distributed computing) . Strong system design abilities with a track record of designing robust, maintainable architectures is a must.
• LLM/AI Application Experience: Proven experience building applications that leverage large language models or generative AI. You have spent time prompting and integrating language models into real products (e.g. building chatbots, semantic search, AI assistants) and understand their behavior and failure modes . Demonstrable projects or work in LLM-powered application development – especially using techniques like RAG or building LLM-driven agents – will make you stand out .
• AI/ML Knowledge: Prioritize applied LLM product engineering over traditional ML pipelines. Strong chops in prompt design, function calling/structured outputs, tool use, context-window management, and the RAG levers that matter (document parsing/chunking, metadata, re-ranking, embedding/model selection). Make pragmatic model/provider choices (hosted vs. open) using latency, cost, context length, safety, and rate-limit trade-offs; know when simple prompting/config changes beat fine-tuning, and when lightweight adapters or fine-tuning are justified. Design evaluation that mirrors product outcomes: golden sets, automated prompt unit tests, offline checks, and online A/Bs for helpfulness/correctness/safety; track production proxies like retrieval recall and hallucination rate. Solid understanding of embeddings, tokenization, and vector search fundamentals, plus working literacy in transformers to reason about capabilities/limits. Familiarity with agent patterns (planning, tool orchestration, memory) and guardrail/safety techniques.
• Tooling & Frameworks: Hands-on experience with the AI/LLM tech stack and libraries. This includes proficiency with LLM orchestration libraries such as LangChain, LlamaIndex, etc., for building prompt pipelines . Experience working with vector databases or semantic search (e.g. Pinecone, Chroma, Milvus) to enable retrieval-augmented generation is highly desired.
• Cloud & DevOps: Own the productionization of LLM/RAG-backed services as high-availability, low-latency backends. Expertise in AWS (e.g., ECS/EKS/Lambda, API Gateway/ALB, S3, DynamoDB/Postgres, OpenSearch, SQS/SNS/Step Functions, Secrets Manager/KMS, VPC) and infrastructure-as-code (Terraform/CDK). You’re comfortable shipping stateless APIs, event-driven pipelines, and retrieval infrastructure (vector stores, caches) with strong observability (p95/p99 latency, distributed tracing, retries/circuit breakers), security (PII handling, encryption, least-privilege IAM, private networking to model endpoints), and progressive delivery (blue/green, canary, feature flags). Build prompt/config rollout workflows, manage token/cost budgets, apply caching/batching/streaming strategies, and implement graceful fallbacks across multiple model providers.
• Product and Domain Experience: Experience building enterprise (B2B SaaS) products is a strong plus . This means you understand considerations like user experience, scalability, security, and compliance. Past exposure to these types of products will help you design AI solutions that cater to a range of end-users.
• Strong Communication & Collaboration: Excellent interpersonal and communication skills, with an ability to explain complex AI concepts to non-technical stakeholders and create clarity from ambiguity . You work effectively in cross-functional teams and can coordinate with product, design, and ops teams to drive projects forward.
• Problem-Solving & Autonomy: Self-motivated and able to manage multiple priorities in a fast-paced environment . You have a demonstrated ability to troubleshoot complex systems, debug issues across the stack, and quickly prototype solutions. A “figure it out” attitude and creative approach to overcoming technical challenges are key.

Preferred (Bonus) Qualifications

• Multi-Modal and Agents: Experience developing complex agentic systems using LLMs (for example, multi-agent systems or integrating LLMs with tool networks) is a bonus . Similarly, knowledge of multi-modal AI (combining text with vision or other data) could be useful as we expand our product capabilities.
• Startup/Agile Environment: Prior experience in an early-stage startup or similarly fast-paced environment where you’ve worn multiple hats and adapted to rapid changes . This role will involve quick iteration and evolving requirements, so comfort with ambiguity and agility is valued.
• Community/Research Involvement: Active participation in the AI community (open-source contributions, research publications, or blogging about AI advancements) is appreciated. It demonstrates passion and keeps you at the cutting edge. If you have published research or have a portfolio of AI side projects, let us know !

Perks of working at Certa.ai:

• Best-in-class compensation
• Fully-remote work with flexible schedules
• Continuous learning
• Massive opportunities for growth
• Yearly offsite
• Quarterly hacker house
• Comprehensive health coverage
• Parental Leave
• Latest Tech Workstation
• Rockstar team to work with (we mean it!)

About the Role:

We are building cutting-edge AI products designed for enterprise-scale applications and arelooking for a Senior Python Developer to join our core engineering team. You will beresponsible for designing and delivering robust, scalable backend systems that power ouradvanced AI solutions.

Key Responsibilities:

• Design, develop, and maintain scalable Python-based backend applications and services.
• Collaborate with AI/ML teams to integrate machine learning models into production environments.
• Optimize applications for performance, reliability, and security.
• Write clean, maintainable, and testable code following best practices.
• Work with cross-functional teams including Data Science, DevOps, and UI/UX to ensure seamless delivery.
• Participate in code reviews, architecture discussions, and technical decision-making.
• Troubleshoot, debug, and upgrade existing systems.

Required Skills & Experience:

• Minimum 5 years of professional Python development experience.
• Strong expertise in Django / Flask / FastAPI.
• Hands-on experience with REST APIs, microservices, and event-driven architecture.
• Solid understanding of databases (PostgreSQL, MySQL, MongoDB, Redis).
• Familiarity with cloud platforms (AWS / Azure / GCP) and CI/CD pipelines.
• Experience with Gen AI tools such as RAG, LLM, Langchain, Langraph etc
• Experience with AI/ML pipeline integration is a strong plus.
• Strong problem-solving and debugging skills.
• Excellent communication skills and ability to work in a collaborative environment.

Good to Have:

• Experience with Docker, Kubernetes.
• Exposure to message brokers (RabbitMQ, Kafka).
• Knowledge of data engineering tools (Airflow, Spark).
• Familiarity with Neo4j or other graph databases.

Relevant Experience:

• 3-5 years

Required Skills

• In-depth experience with Python and OO concepts

• Experience with using NumPy, Pandas, or similar AI/ML libraries

• Deep understanding of multi-process architecture and threading limitations of Python

• Expert knowledge of Python and related frameworks including Django and Flask.

• Experience in Machine Learning and Artificial Intelligence

• Good understanding of relational data modeling concepts and comfortable with SQL

• databases.

• Good understanding of AWS / Azure cloud

• Nice to have

• Experience / Exposure in Chat BOT or Voice BOT

• Experience in Lambda Function OR Azure Functions

• Exposure to Financial Domain

Additional Skillsets Desired:

• Ability to work with clients and key stakeholders to ensure requirements are met

• Strong problem-solving and debugging skills

• Passion to work in a start-up environment and readiness to dabble with challenging

• Ability to work in both a solo and team environment

• Proven ability to communicate technical information coherently, both verbally and into internal team and external customers, maintaining a customer focused

Who Are We

A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.

ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.

WHY US

• Join top AI company
• Grow with your best companions
• Continuous pursuit of excellence, equality, respect
• Competitive compensation and benefits

You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.

To learn more about how we work, please check out

https://www.orbo.ai/">https://www.orbo.ai/.

We at Orbo are looking for developers who have passion for technology, ability to deploy new and novel technologies in environments that are often low on humans as well as capital. From solving complex algorithm problems, software development engineers also develop complex algorithms to solve real-life crises and are involved in the system design of several applications and thus contributing to their technical architecture. 

CTC- Upto 12 LPA

• To determine the scope of software development projects.
• Collaborating with the software development team on application design and development.
• Developing software and overseeing the deployment of applications across platforms.
• Performing diagnostic tests and debugging procedures.
• Creating end-user application feedback channels.
• Optimizing software by performing maintenance, updates, and upgrades.
• Documenting processes and maintaining software development records.
• Keeping up to date with C++ standards and advancements in application development.

• Bachelor's degree in computer science, information systems, or similar.
• Strong understanding of OOPs, SDL.

• Problem solving with data structure and algorithms.
• Build tools(make/Cmake/Ninja/Bazel)
• Experience with OS & hardware specific development (SIMD, AVX, AVX2)
• Having knowledge of 3rd Party library integration (OpenCV, Tensorflow, NCNN, TNN, liptorch, Openvino, ONNX runtime)
• Worked with Modern C++ 
• Worked with Linux & Windows
• Experience with multi threading and multi processing 
• Superb analytical and problem-solving skills.
• Excellent collaboration and communication skills.
• Great organizational and time management skills.

Should be highly Technical and hands-on experience in Artificial Intelligence and Machine learning and Python. Managing the successful delivery of projects by efficient planning and coordination.

KEY RESPONSIBILITIES OF THE POSITION :

• Create Technical Design for AI, Machine Learning, Deep Learning, NLP, NLU, NLG projects and implement the same in production.
• Solid understanding and experience of deep learning architectures and algorithms
• Working experience with AWS, most importantly AWS SageMaker, Aurora or MongoDB, Analytics and reporting.
• Experience solving problems in the industry using deep learning methods such as recurrent neural networks (RNN, LSTM), convolutional neural nets, auto-encoders, etc.
• Should have experience of 2-3 production implementations of machine learning projects.
• Knowledge of open-source libraries such as Keras, Tensor Flow, Pytorch
• Work with business analysts/consultants and other necessary teams to create a strong solution
• Should have in-depth understanding and experience of Data Science and Machine Learning projects using Python, R, etc. Skills in Java/C are a plus
• Should developing solutions using python in AI/ML projects
• Should be able to train and build a team of technical developers
• Desired to have experience as leads in designing and developing applications/tools using Microsoft technologies - ASP.Net, C#, HTML5, MVC
• Desired to have knowledge on any of the cloud solutions such as Azure or AWS
• Desired to have knowledge on any of container technology such as Docker
• Should be able to build strong relationships with project stakeholders

Keywords:

• Python
• Artificial Intelligence
• Machine Learning
• AWS
• Django
• NLP

• Writing efficient, reusable, testable, and scalable code
• Understanding, analyzing, and implementing – Business needs, feature modification requests, conversion into software components
• Integration of user-oriented elements into different applications, data storage solutions
• Developing – Backend components to enhance performance and receptiveness, server-side logic, and platform, statistical learning models, highly responsive web applications
• Designing and implementing – High availability and low latency applications, data protection and security features
• Performance tuning and automation of application
• Working with Python libraries like Pandas, NumPy, etc.
• Creating predictive models for AI and ML-based features
• Keeping abreast with the latest technology and trends
• Fine-tune and develop AI/ML-based algorithms based on results

Good proficiency in,

• Python frameworks like Django, etc.
• Web frameworks and RESTful APIs
• Core Python fundamentals and programming
• Code packaging, release, and deployment
• Database knowledge
• Circles, conditional and control statements
• Object-relational mapping
• Code versioning tools like Git, Bitbucket

Fundamental understanding of,

• Front-end technologies like JS, CSS3 and HTML5
• AI, ML, Deep Learning, Version Control, Neural networking
• Data visualization, statistics, data analytics
• Design principles that are executable for a scalable app
• Creating predictive models
• Libraries like Tensorflow, Scikit-learn, etc
• Multi-process architecture
• Basic knowledge about Object Relational Mapper libraries
• Ability to integrate databases and various data sources into a unified system
• Basic knowledge about Object Relational Mapper libraries
• Ability to integrate databases and various data sources into a unified system