Technical Architect/CTO

About Techjays

At Techjays, we build production-grade AI platforms for global clients. We operate at the intersection of backend engineering, distributed systems, and applied AI — delivering secure, scalable, and enterprise-ready intelligent systems. Our team has built and scaled products at Google, Akamai, NetApp, ADP, Cognizant, and Capgemini.

About the Role

This is not a feature-delivery role. We are looking for an AI Lead who can architect, own, and scale intelligent backend systems end-to-end. You will drive both technical direction and execution — working across LLM integrations, RAG pipelines, agentic AI workflows, and cloud-native backend systems for global clients.

What You'll Do

• Architect and scale backend systems powering AI-driven applications
• Design and implement RAG pipelines, AI agents, and LLM integrations
• Own systems end-to-end — from architecture to deployment and scaling
• Integrate and optimize LLMs (Claude, GPT, Gemini) for real-world production use cases
• Build high-performance distributed systems with observability and cost efficiency
• Lead backend and AI initiatives with strong technical ownership
• Mentor engineers and raise the technical bar across teams
• Collaborate with product and AI teams to deliver AI-native solutions

What We're Looking For

• 6–10 years of strong backend engineering experience
• Hands-on expertise in Python (FastAPI / Django / Flask)
• Deep understanding of Generative AI and LLM-based systems
• Strong experience with RAG pipelines and Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Solid knowledge of Agentic AI — building autonomous agents and multi-agent workflows
• Proficiency in AWS or GCP in production environments
• Experience with distributed systems, microservices, and system design
• Strong grasp of Data Structures, Algorithms, and Design Patterns
• Familiarity with WebSockets, Git, Linux/Unix, and CI/CD

Nice to Have

• Experience with Anthropic Claude API and Claude Code
• Familiarity with real-time data systems or streaming (Kafka, etc.)
• MLOps and AI system lifecycle experience
• Optimizing AI systems for latency, cost, and scalability

Who You Are

• You think in systems, not just features
• You take full ownership of what you build
• You are comfortable navigating fast-moving, ambiguous environments
• You stay updated with the latest in Generative AI and backend technologies
• Strong communicator who can collaborate across teams and global clients

What We Offer

• Competitive compensation (Best in Industry)
• Work on production-grade AI systems used by global clients
• Exposure to cutting-edge AI tools and frameworks
• A culture that values clarity, integrity, and continuous growth

Responsible for developing, enhancing, modifying, and maintaining chatbot applications in the Global Markets environment. The role involves designing, coding, testing, debugging, and documenting conversational AI solutions, along with supporting activities aligned to the corporate systems architecture.

You will work closely with business partners to understand requirements, analyze data, and deliver optimal, market-ready conversational AI and automation solutions.

Key Responsibilities

• Design, develop, test, debug, and maintain chatbot and virtual agent applications
• Collaborate with business stakeholders to define and translate requirements into technical solutions
• Analyze large volumes of conversational data to improve chatbot accuracy and performance
• Develop automation workflows for data handling and refinement
• Train and optimize chatbots using historical chat logs and user-generated content
• Ensure solutions align with enterprise architecture and best practices
• Document solutions, workflows, and technical designs clearly

Required Skills

• Hands-on experience in developing virtual agents (chatbots/voicebots) and Natural Language Processing (NLP)
• Experience with one or more AI/NLP platforms such as:
• Dialogflow, Amazon Lex, Alexa, Rasa, LUIS, Kore.AI
• Microsoft Bot Framework, IBM Watson, Wit.ai, Salesforce Einstein, Converse.ai
• Strong programming knowledge in Python, JavaScript, or Node.js
• Experience training chatbots using historical conversations or large-scale text datasets
• Practical knowledge of:
• Formal syntax and semantics
• Corpus analysis
• Dialogue management
• Strong written communication skills
• Strong problem-solving ability and willingness to learn emerging technologies

Nice-to-Have Skills

• Understanding of conversational UI and voice-based processing (Text-to-Speech, Speech-to-Text)
• Experience building voice apps for Amazon Alexa or Google Home
• Experience with Test-Driven Development (TDD) and Agile methodologies
• Ability to design and implement end-to-end pipelines for AI-based conversational applications
• Experience in text mining, hypothesis generation, and historical data analysis
• Strong knowledge of regular expressions for data cleaning and preprocessing
• Understanding of API integrations, SSO, and token-based authentication
• Experience writing unit test cases as per project standards
• Knowledge of HTTP, REST APIs, sockets, and web services
• Ability to perform keyword and topic extraction from chat logs
• Experience training and tuning topic modeling algorithms such as LDA and NMF
• Understanding of classical Machine Learning algorithms and appropriate evaluation metrics
• Experience with NLP frameworks such as NLTK and spaCy

1.   In-Depth knowledge and experience with C# .NET Core are must.

2.   Experience in working with API Gateways, REST, SOAP, OAuth, SAML.

3.   Experience inworking with Kafka based environment.

4.   Microservices and Event driven Architecture (with a focus on cloud).

5.   Experience and understanding of OOPS and SOLID design principals.

6.   Well verse with Design Patterns.

7.   Familiarity with Azure and AWS offerings.

8.   Understanding of Relational and NoSQL databases SQL Server, Azure SQL, MongoDB, Elastic.

9.   Familiarity with the .NET framework

10. Familiar with various design and architectural patterns

11. Knowledge of concurrency patterns in C#

12. A willingness to get trained and work on cutting edge technologies like React, Node etc.

13. Understanding fundamental design principles behind a scalable application

14. Implementing automated testing platforms and unit tests

15. Proficient understanding of code versioning tools Git

Familiarity with CICD tools, JIRA, Azure devops etc

• Augmenting, improving, redesigning, and/or re-implementing Dolat's low-latency/high-throughput production trading environment, which collects data from and disseminates orders to exchanges around the world
• Optimizing this platform by using network and systems programming, as well as other advanced techniques
• Developing systems that provide easy access to historical market data and trading simulations
• Building risk-management and performance-tracking tools
• Shaping the future of Dolat through regular interviewing and infrequent campus recruiting trips
• Implementing domain-optimized data structures
• Learn and internalize the theories behind current trading system
• Participate in the design, architecture and implementation of automated trading systems
• Take ownership of system from design through implementation

• 3 - 6 Years of Experience in Golang Development
• Understands requirements well and comes up with an efficient design
• Develops complex, well-backed and bug-free products.
• Estimates accurately.
• Takes well-reasoned tech decisions keeping in mind goals and trade-offs
• Become a go-to person in more than one area. Provide technical mentoring to team
• Communicates clearly, gets clarifications, and establishes expectations for all parties
• Helps establish SDLC best practices and high standards of code quality
• Demonstrates excellent problem solving & debugging skills
• Proactively identifies and resolves issues in requirements, design, and code

Ideal Candidate Profile:

• Solid experience in Golang is a must.
• Solid understanding of Apache Products.
• Should have experience in cloud computing (AWS is desired).
• Has an ability to quickly learn and contribute in multiple codebases
• Overcomes roadblocks and requires minimal oversight
• Takes initiatives to fix issues/tech debts before assigned to him/her
• Able to deep dive into the codebase and advise QA of possible regression impact
• Communicates tech decisions through design docs and tech talks
• Has delivered projects with end-to-end accountability
• Keeps track of industry trends and introduces the right tech/ tools for a given job
• Excellent understanding of software engineering practices,
• Design Patterns, Data Structures, Algorithms
• Experience in product-driven organization