### Responsibilities:
* Design and contribute to workflow implementations
* Champion workflow orchestration best practices
* Build software as part of a nimble agile Team where you have every opportunity to make an impact on the bottom line and contribute to the architecture.
* Ensure our infrastructure is safely extensible, scalable, reliable and meets SLAs for both external and internal users.
* Ensure our solutions are testable, intuitive, and easy to maintain.
* Use state of the art tools for remote collaboration and developer happiness, i.e., IntelliJ CodeWithMe and Tuple
* Design, build, and operationalize Generative AI capabilities (LLM-powered services) with strong focus on security, reliability, and scalability.
* Implement Retrieval-Augmented Generation (RAG) patterns (ingestion, chunking, embeddings, vector search, reranking) to ground LLM outputs in enterprise knowledge.
* Develop and integrate LLM tool/function-calling ("agents") to orchestrate workflows across internal APIs and services while enforcing least-privilege access.
* Leverage Model Context Protocol (MCP) servers/tools (or equivalent patterns) to standardize how LLM applications access data sources and operational tools.
* Establish evaluation, monitoring, and guardrails for GenAI (prompting standards, hallucination mitigation, PII controls, red-teaming, offline/online metrics).
* Participate in design and code reviews for key components and cross Enterprise initiatives.
### Qualifications:
* 8-13 years of software development experience, and preferably a Bachelor's or master's degree in computer science, computer engineering, or other technical discipline.
* Team player and a hands-on engineer.
* Experience mentoring and coaching junior engineers.
* Experience in designing and implementing highly scalable, low latency Java / Go based applications.
* Hands on experience in multi-threading programming.
* Hands-on experience building LLM-based applications using at least one major model/provider, and applying prompt engineering, structured outputs, and tool/function calling.
* Experience designing and implementing RAG systems, including document ingestion pipelines, embeddings, vector search, and relevance tuning.
* Experience integrating LLM applications with tools and enterprise systems (APIs, databases, queues) and familiarity with MCP concepts/servers for tool and context access.
* Understanding of GenAI security and risk controls (PII handling, prompt injection, data leakage), and experience with evaluation/observability of LLM systems.
* Basic high availability techniques and implementation knowledge.
* Practical knowledge of caching and distributed systems.
* Staying in touch with industry standards and current technologies is expected.
* Experience in profiling / performance analysis of applications.
* Core competencies in distributed technologies including Java, Spring, APIs (REST), JSON, XML, Kafka, JDBC, MongoDB, Postgres, NoSQL databases, Spring Boot, Spring Batch, JUnit, Jenkins, and Gradle/Maven.
* Experience with In-memory computing solutions is a big plus.
* Commitment to software practices of continuous Integration, automated/repeatable testing, and collaborative work environments.
* Ability to think abstractly and deal with ambiguous/under-defined problems.
* Ability to enable business capabilities through innovation.
* Demonstrated willingness to learn innovative technologies and takes pride in how fast they develop working software.
* Experience working with streaming solutions is highly desirable (preferably Apache Kafka and Kafka Streams).
* Hands-on experience in full-stack software development is desirable.
* Hands on experience in Big Data technologies including Python, Hadoop, and Spark is a plus
* Have excellent written and verbal communications skills.
* Familiarity with CI/CD pipelines and DevOps tools (Jenkins, GitLab).
### Preferred Qualifications:
* Experience with container orchestration tools like Kubernetes and Docker.
* Previous experience with payment systems or real-time transaction platforms.
* Leadership experience in a fast-paced development environment.
* Experience in API development for fintech applications.
* Experience with vector databases and search stacks (e.g., OpenSearch/Elasticsearch, pgvector, Pinecone, Weaviate) and embedding lifecycle management.
* Experience building LLM agents with tool/function calling, including workflow orchestration, retries, and safe fallbacks.
* Experience creating/operating MCP servers (or similar abstractions) to expose enterprise data and actions to LLM applications with strong authentication/authorization.
* Familiarity with LLM evaluation techniques (golden datasets, human review workflows, automated scoring) and safety guardrails for regulated environments.